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Location: New York, New York; Manhattan, New York; Brooklyn, New York; Trenton, New Jersey; Yonkers, New york; New York City Metropolitan Area; Newark, New Jersey Workplace: remote Provectus is a Premier AWS partner and an Anthropic Strategic Partner, helping enterprises across Financial Services and Life Sciences design, build, and operate production AI systems. Our Forward Deployed Engineering model lets us embed with clients and deliver AI outcomes, not just advice. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. We are looking for an Alliances Team Lead to own and grow Provectus's most strategic partnerships: Anthropic and AWS. This is a build-and-lead role — you will create the programs for our alliances function from the ground up. On the Anthropic side, you will run partner activation programs end to end: identify target accounts, align scope with Anthropic partner teams, coordinate delivery, and ensure funding milestones and closeout requirements are met. You will grow our standing in the Claude Partner Network and be the person inside Anthropic who advocates for Provectus. On the AWS side, you will manage the alliance, maintaining AI and generative AI competency requirements, keeping Premier Tier standing current, and building the co-sell motion with AWS field teams. There is also an opportunity to develop early-stage partnerships with GCP and others as the ecosystem evolves. You will lead a team and work directly with Provectus engineering, SO, and marketing leadership to turn partner programs into measurable pipeline. Responsibilities: Anthropic partnership Own the Anthropic partnership end-to-end — build and scale partner activation programs, manage funded enablement engagements from scoping through completion and reimbursement. Create repeatable playbooks for partner-funded customer activations: identify target accounts, align scope with Anthropic partner teams, coordinate delivery, and ensure funding milestones are met. Grow Provectus's standing in the Claude Partner Network; track program changes, tier requirements, and new co-marketing opportunities. Develop named executive relationships at Anthropic — field leadership, partner success, and product teams — who actively advocate for Provectus in joint accounts. AWS alliance Manage the AWS alliance day-to-day — keep Provectus current on Generative AI competency requirements, renewals, and program changes; maintain Premier Tier standing. Build and expand co-sell motion with AWS field teams — drive opportunity registration, joint account planning, and pipeline reviews with AWS partner sellers. Manage AWS funding programs; ensure Provectus maximises available program benefits. Team and cross-functional leadership Lead and develop a team of partner managers; set priorities, coach on partner engagement, and build the operating cadence for the alliances function. Work with sales, marketing, and delivery to turn partner programs into pipeline — co-marketing campaigns, joint solution offerings, and partner-sourced revenue. Represent Provectus at executive briefings and ecosystem events; bring relevant partner intelligence back to leadership. Ecosystem expansion Identify and develop early-stage partnerships with GCP and other emerging AI ecosystem players as the market evolves. Track the competitive alliance landscape — which SI competitors hold which partner tiers, where there are white spaces Provectus can occupy. What You Need to Succeed: 5–8+ years in technology alliances, partnerships, or channel roles, with meaningful time spent managing a hyperscaler relationship (Anthropic, AWS strongly preferred). Direct experience with partner programs: competencies, funding programs (MDF, MAP, or similar), co-sell mechanisms, and partner portals — hands-on, not just supervisory. Track record of building alliance programs from scratch — not just inheriting and running an existing book. Experience leading and developing a team; comfortable setting direction and coaching without a large management structure behind you. Comfortable operating at executive level with partners and customers, and hands-on enough to manage program mechanics personally when needed. Strong written and verbal communication — able to translate partner programs into clear internal playbooks and joint value propositions. Familiarity with the AI/ML ecosystem — enough to have credible conversations about implementation approaches and enterprise AI adoption challenges. Vertical depth in Financial Services or Life Sciences — Anthropic's and Provectus's primary enterprise target markets. Experience managing GCP, OpenAI, or other emerging AI ecosystem partnerships is preferred. Willingness to travel (up to 40%) for customer meetings, executive briefings, onsite workshops, conferences, and other business development activities. What success looks like: Anthropic activation programs running as a repeatable, funded motion with a growing pipeline of customer engagements quarter over quarter. AWS AI competency requirements current, with Premier Tier standing maintained and co-sell pipeline growing quarter over quarter. Named executive relationships at both partners who actively advocate for Provectus in joint accounts. An alliances team with clear ownership, operating cadence, and measurable partner-sourced revenue contribution. About Provectus: Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI and data-driven innovation organization-wide in such industries as Financial Services, Insurance, Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, and Manufacturing. We are recognized by industry analysts as a leading provider of AI solutions across key business domains. At Provectus, we value innovation, ownership, and collaboration — and we are looking for people who want to grow with us and make an impact. Why Join Us: Genuine autonomy and the trust to operate in your lane without micromanagement. World-class AI/ML delivery capability behind you — a team that can actually execute on what you sell or source. You will shape how a fast-growing AI consultancy goes to market at a defining moment for enterprise AI adoption. High-impact role with direct visibility to leadership. Strong earning potential with performance-based bonuses. Opportunity to work with cutting-edge AI and cloud solutions. B2B contract model or full-time model. OTE range $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data. Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan.

Location: Philadelphia, Pennsylvania; Massachusetts; Maryland; Connecticut; Rhode Island; Delaware; New Jersey Workplace: remote Provectus is a Premier AWS partner and an Anthropic Strategic Partner, helping enterprises across Financial Services and Life Sciences design, build, and operate production AI systems. Our Forward Deployed Engineering model lets us embed with clients and deliver AI outcomes, not just advice. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. We are looking for an Alliances Team Lead to own and grow Provectus's most strategic partnerships: Anthropic and AWS. This is a build-and-lead role — you will create the programs for our alliances function from the ground up. On the Anthropic side, you will run partner activation programs end to end: identify target accounts, align scope with Anthropic partner teams, coordinate delivery, and ensure funding milestones and closeout requirements are met. You will grow our standing in the Claude Partner Network and be the person inside Anthropic who advocates for Provectus. On the AWS side, you will manage the alliance, maintaining AI and generative AI competency requirements, keeping Premier Tier standing current, and building the co-sell motion with AWS field teams. There is also an opportunity to develop early-stage partnerships with GCP and others as the ecosystem evolves. You will lead a team and work directly with Provectus engineering, SO, and marketing leadership to turn partner programs into measurable pipeline. Responsibilities: Anthropic partnership Own the Anthropic partnership end-to-end — build and scale partner activation programs, manage funded enablement engagements from scoping through completion and reimbursement. Create repeatable playbooks for partner-funded customer activations: identify target accounts, align scope with Anthropic partner teams, coordinate delivery, and ensure funding milestones are met. Grow Provectus's standing in the Claude Partner Network; track program changes, tier requirements, and new co-marketing opportunities. Develop named executive relationships at Anthropic — field leadership, partner success, and product teams — who actively advocate for Provectus in joint accounts. AWS alliance Manage the AWS alliance day-to-day — keep Provectus current on Generative AI competency requirements, renewals, and program changes; maintain Premier Tier standing. Build and expand co-sell motion with AWS field teams — drive opportunity registration, joint account planning, and pipeline reviews with AWS partner sellers. Manage AWS funding programs; ensure Provectus maximises available program benefits. Team and cross-functional leadership Lead and develop a team of partner managers; set priorities, coach on partner engagement, and build the operating cadence for the alliances function. Work with sales, marketing, and delivery to turn partner programs into pipeline — co-marketing campaigns, joint solution offerings, and partner-sourced revenue. Represent Provectus at executive briefings and ecosystem events; bring relevant partner intelligence back to leadership. Ecosystem expansion Identify and develop early-stage partnerships with GCP and other emerging AI ecosystem players as the market evolves. Track the competitive alliance landscape — which SI competitors hold which partner tiers, where there are white spaces Provectus can occupy. What You Need to Succeed: 5–8+ years in technology alliances, partnerships, or channel roles, with meaningful time spent managing a hyperscaler relationship (Anthropic, AWS strongly preferred). Direct experience with partner programs: competencies, funding programs (MDF, MAP, or similar), co-sell mechanisms, and partner portals — hands-on, not just supervisory. Track record of building alliance programs from scratch — not just inheriting and running an existing book. Experience leading and developing a team; comfortable setting direction and coaching without a large management structure behind you. Comfortable operating at executive level with partners and customers, and hands-on enough to manage program mechanics personally when needed. Strong written and verbal communication — able to translate partner programs into clear internal playbooks and joint value propositions. Familiarity with the AI/ML ecosystem — enough to have credible conversations about implementation approaches and enterprise AI adoption challenges. Vertical depth in Financial Services or Life Sciences — Anthropic's and Provectus's primary enterprise target markets. Experience managing GCP, OpenAI, or other emerging AI ecosystem partnerships is preferred. Willingness to travel (up to 40%) for customer meetings, executive briefings, onsite workshops, conferences, and other business development activities. What success looks like: Anthropic activation programs running as a repeatable, funded motion with a growing pipeline of customer engagements quarter over quarter. AWS AI competency requirements current, with Premier Tier standing maintained and co-sell pipeline growing quarter over quarter. Named executive relationships at both partners who actively advocate for Provectus in joint accounts. An alliances team with clear ownership, operating cadence, and measurable partner-sourced revenue contribution. About Provectus: Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI and data-driven innovation organization-wide in such industries as Financial Services, Insurance, Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, and Manufacturing. We are recognized by industry analysts as a leading provider of AI solutions across key business domains. At Provectus, we value innovation, ownership, and collaboration — and we are looking for people who want to grow with us and make an impact. Why Join Us: Genuine autonomy and the trust to operate in your lane without micromanagement. World-class AI/ML delivery capability behind you — a team that can actually execute on what you sell or source. You will shape how a fast-growing AI consultancy goes to market at a defining moment for enterprise AI adoption. High-impact role with direct visibility to leadership. Strong earning potential with performance-based bonuses. Opportunity to work with cutting-edge AI and cloud solutions. B2B contract model or full-time model. OTE range $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data. Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan.

Location: New York; New Jersey Workplace: hybrid About the Role: The hiring problem you'd be solving We build AI systems that enterprises run their business on. Production systems inside banks, insurers, and health systems, where our engineers embed with the client, learn the work, and own the outcome. We call them Forward Deployed Engineers and Forward Deployed Executives. These people hold design conversations with a Chief Data Officer on Tuesday and ship to production next Monday. We are hiring a Recruiter to help us scale our FDE/FDX, Product, and GTM teams. Beyond filling roles, you will help build the community around Provectus. You'd own our US talent community strategy. Five open reqs at a time, none of them generic. We would rather you run five properly than twenty badly. Location: Hybrid, New York: 2-3 days onsite Type: Full-time (W2) or contract What You'll Do: Full-cycle hiring across the US for Forward Deployed Engineers (software, AI/ML, architects, leads), Forward Deployed Executives, Product Owners, and Business Development Managers. Intake to offer. Direct sourcing as the primary channel. LinkedIn, GitHub, community channels, referrals. Passive candidates doing the most consequential AI work, not the ones already looking. You'll build and keep the talent maps for these profiles in financial services, insurance, healthcare, and life sciences. Partnership with the hiring managers. You'll run calibration with them and bring market data when a scorecard doesn't match what exists. Architect and execute Provectus's talent community strategy in the US. Meetups, workshops, hackathons, university programs, and the AI/ML communities our candidates actually spend time in, so the engineers we want know who we are before we reach out. You don't need to have run events before. You need to want to help with that, and there's a budget and support from marketing when you do. The US hiring picture. Talent market intelligence, compensation benchmarking, and how we position Provectus against the companies competing for the same engineers. What you'll bring: 2+ years of full-cycle recruiting, ideally somewhere technical, fast-moving, or consulting-shaped Proven track record hiring senior technical profiles — AI/ML engineers, software engineers, architects, or consulting leaders Direct sourcing as a real skill. You can build a market map from scratch and write outreach a senior engineer actually answers. You already use AI in your own workflow. Come ready to show us what and how. This is one place where being early in your career is often an advantage. Excellent communication and stakeholder management skills Highly organized and comfortable with ambiguity in a distributed, global team Based in the New York / New Jersey area and able to be onsite [2-3] days a week Nice to have: experience at a consultancy or embedded delivery model, GTM or sales hiring, prior event or community building. Where this goes: This is a growing US function. The person who does this well takes on more of the community mandate, more senior searches, and a path toward owning the US talent function. We'll talk about that trajectory. What We Offer: Direct impact on Provectus's growth in the US market with direct visibility to leadership. Access to the Provectus Learning Hub, Claude Code certification support, and access to Anthropic's frontier models as part of our Strategic Partnership Collaborative culture that rewards ownership, curiosity, and continuous learning B2B contract model or Full-time W2 model. Base $120-150k. Final offer reflects experience, skills, and market data. Health, vision, and dental insurance; 401(k) matching; unlimited vacation; 401(K) matching plan (in case W2). About Provectus: Provectus is an AWS Premier Partner and an Anthropic Strategic Partner working at the front edge of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable outcomes through bespoke applications, managed services, and advisory work. We focus on Financial Services & Insurance and Healthcare & Life Sciences, with offices across North America, LATAM, and EMEA. Hiring process: 30-minute intro call with Head of Talent Acquisition 60-minute deep dive into your experience and a conversation about one of our live reqs and how you'd approach that market 30-minute call with a Head of People Operations On-site meeting with the CEO

Location: Colombia; Costa Rica Workplace: remote Provectus is a Premier AWS Partner and an Anthropic partner, featured in Forrester's AI Technical Services Landscape. We are roughly 420 engineers building production AI for enterprise clients in Financial Services, Healthcare and Life Sciences, Retail, and Entertainment. We build custom systems on live client data, not off the shelf products and not demos. We are opening a Solution Owner seat on our Delivery team in Colombia and Costa Rica. This is an early career seat, but it is not a training seat. You will sit between the client and the engineering team on a real engagement, own a slice of scope, and be expected to figure out the next step yourself. The profile we are looking for is specific: you started technical, as a software, data, or ML engineer, and you have already moved toward the business side of building products, or you are ready to make that move now. You are the person on the team who automates their own work with AI tools before anyone asks. What You Will Do: Own a defined slice of a client engagement, from use case framing through backlog, release, and result Run discovery sessions and workshops with client stakeholders, and turn what you hear into written scope engineers can build against Translate technical constraints into business language, and business goals into technical requirements Maintain a groomed backlog with sized, technically specific stories, and drive sprint planning and release cadence Prototype rapidly on live client data using our delivery stack, including Claude, Claude Code, MCP servers, and Skills Work alongside GenAI and agentic AI builds, including RAG, agent workflows, and LLM integrations, closely enough to judge quality and explain trade offs Define success metrics for your slice of scope and report progress honestly, including when something is not working Build reusable artifacts, demos, and documentation so the next engagement starts faster than yours did Partner with Principal Architects, Forward Deployed Engineers, and account teams across US and LATAM time zones What You Will Bring: 2 to 4 years of total professional experience, including hands on engineering time as a software, data, or ML engineer At least 1 year in a product, delivery, or client facing role such as Product Owner, Technical Product Owner, Business Analyst, Delivery Lead, or equivalent Daily use of GenAI tools in your own workflow, Claude and Claude Code preferred, with concrete examples of workflows you redesigned Ability to read code and technical documentation well enough to hold a real conversation with senior engineers Practical Agile and Scrum experience: backlog, sprints, planning, retrospectives Written and spoken English at B2 or above, comfortable leading a client call without a manager in the room Self direction as a default. You are given a goal and ambiguity, not a task list, and you move anyway Based in Colombia or Costa Rica Nice to Have: Exposure to Financial Services and Insurance or Healthcare and Life Sciences clients Working understanding of GenAI concepts: prompt engineering, RAG, embeddings, vector databases, agentic patterns Familiarity with AWS, especially Bedrock, SageMaker, Lambda, or S3 Experience shipping an LLM or RAG feature that reached real users Experience building your own automations, scripts, MCP integrations, or internal tools Consulting or professional services background Certifications such as CSPO, SAFe PO/PM, or AWS Cloud Practitioner What We Offer: Real client delivery on frontier AI from month one, not shadowing Direct access to Principal Architects and Forward Deployed Engineers as your working peers Anthropic and AWS partnership work, with early access to tooling and premium AI subscriptions Internal training programs and full support for AWS and Claude certifications A clear growth path toward Senior Solution Owner or Solutions Architecture Remote work with flexible hours across US and LATAM overlap Long term B2B collaboration Equipment budget and all the tooling you need

Location: San Francisco Bay Area, California; New York City Metropolitan Area Workplace: remote About the role: Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. We embed engineers and leaders inside client operations as Forward Deployed Engineers (FDE) and Forward Deployed Executives (FDX) — people who learn the work, ship the system, and own the outcome. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Bluprints. You will do the customer’s job before you automate it. Most AI engagements fail the same way: someone gathers requirements, someone writes a PRD, and a team ships a workflow nobody uses. We think the requirements-gathering step is the bug. So we remove it. A Forward Deployed AI Engineer at Provectus spends the first weeks of an engagement in the operator’s seat — as the underwriter, the analyst, the RCM specialist, the claims clinician, whoever actually does the work we’ve been asked to change. You do the job. You learn the constraints from the inside, the ones nobody writes down. Then you sit at a table with that operator and a Forward Deployed Executive and rebuild the function from first principles — and you are the one who builds it. Three things define how you work: Embedded, not engaged . You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Real tasks, not scope . You are not fenced into a siloed deliverable. You go where the operating problem is. Autonomous . Embedded is not staff-augmented. You own the method; nobody hands you a ticket. You won’t start from zero. Provectus builds industry blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. That loop is the difference between an outcome and an invoice. You’ll be measured on whether the Business Unit’s number moved — not on hours, not on scope delivered. This is a role for engineers who have led before — as a founder, a CTO, a staff engineer — and who want to stay in the code while owning the outcome. On most days you’ll be the most senior technical person in the room, and you’ll still be the one shipping. Requirements: 8+ years building software , a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. You will take the operator’s seat. You are genuinely willing to spend weeks doing someone else’s job — claims processing, underwriting, revenue-cycle work — before you write a line of code. Engineers who need to stay in the IDE should not apply. You learn domains fast. Demonstrated ability to become conversant in an unfamiliar business function quickly enough to argue with the people who do it for a living. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD, and the operational reality of a system someone else inherits. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Solid AI/ML foundations — you understand what the models do well enough to reason about failure modes, not just call the API. Strong hands-on prodcution experience with Claude Code/Cowork. Fluent English, written and spoken. Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution. Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management . Consulting, professional services, or other embedded customer-facing delivery. Data platform depth: data lakes, warehouses, streaming and real-time analytics, data mesh and data contracts, governance and data quality. MLOps and classical ML: PyTorch, SageMaker, MLflow. Fine-tuning, distillation, or inference/serving optimization. Graph databases (Neo4j, AWS Neptune). IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Take the seat Do the operator’s job for two to four weeks at the start of an engagement. Learn the function from inside, not from a requirements doc. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow — in weeks, not quarters. Sit with the operator and the Forward Deployed Executive and redesign the function from first principles. Discovery, user research, and PRD-writing collapse into one team that re-imagines its own job. You are all three roles. Build Ship production GenAI systems into the customer’s environment — LLM applications, agentic workflows, retrieval and structured-extraction pipelines, and the services around them. Running software, not recommendations. Build the evaluation harness before you build the feature. When the engagement is bound to a business KPI, “it looked good in testing” is not an answer. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — backend services, data pipelines, and the AI layer. Python and TypeScript are our centre of gravity; we choose tools to fit the customer, not the résumé. Take systems to production on AWS (GCP/Azure where the customer requires it): containerized, observable, and maintainable after we leave. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Own the outcome Work in a pair with a Forward Deployed Executive who carries the Business Unit’s KPIs. Your work is measured against the same number. Drive adoption. A system the BU routes around has not shipped. Change management is part of the engineering job here, not a phase after it. Be credible with the customer’s engineers, their operators, and their executives — and be willing to disagree with all three. Shape what we commit to before we commit to it. You’ll have the standing to do it, because you’re the one who will build it. What We Offer: Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare The chance to shape how leading enterprises adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture High-impact role with direct visibility to leadership. Strong earning potential with performance-based bonuses. Opportunity to work with cutting-edge AI and cloud solutions. B2B contract model or full-time model. Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. OTE range: up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data. How we hire: Intro conversation — the role, your background, what you want to be doing. Two live engineering sessions. Real problems, your own editor. You may use an LLM assistant (ChatGPT, Claude) — how you work now includes these tools. Autocomplete/agentic coding tools are off for these sessions. The redesign session. We hand you an unfamiliar business function and the constraints of the person who performs it. You have to understand the job well enough to rebuild it — then say what you’d build and how you’d know it worked. No LLMs for this one. Team and practice conversation.

Location: North Macedonia; Bosnia and Herzegovina; Czechia; Croatia; Moldova; Bulgaria; Montenegro Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: Ukraine; Spain; Slovakia; Serbia; Yerevan; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: Ukraine; Serbia; Yerevan; Spain; Slovakia; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: North Macedonia; Montenegro; Moldova; Bulgaria; Czechia; Bosnia and Herzegovina; Croatia Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner , working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: New Jersey; New York; Pennsylvania; Connecticut; Massachusetts Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems. Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive. Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented. Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket. Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack. Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name. We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name. What we look for: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits. Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses). Nice to have Containers and orchestration (Kubernetes/ECS) and CI/CD in production. IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it. Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously. You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare. Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice. What We Offer: Full-time. On-site visits to client’s facilities and our office in NYC 1/week Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team. We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates. You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO. How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion.

Location: New York City Metropolitan Area; Connecticut; New Jersey; New York, New York; San Francisco Bay Area, California Workplace: remote Provectus is a Premier AWS partner and an Anthropic Strategic Partner, helping enterprises across Financial Services and Life Sciences design, build, and operate production AI systems. Our Forward Deployed Engineering model lets us embed with clients and deliver AI outcomes, not just advice. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. We are looking for a Business Development & Partner Manager to own two complementary revenue motions simultaneously: converting partner-sourced leads into Provectus clients, and building a self-sourced pipeline from scratch. The first motion sits at the heart of our Anthropic and AWS partnership. They share qualified enterprise leads with us. Your job is to receive those leads, run the full sales cycle, and close them — making Provectus the AI implementation partner of choice for Anthropic's enterprise accounts. Beyond converting inbound leads, you will actively grow the relationship: joint pipeline reviews, co-marketing, partner tier maintenance, and expanding the number of Anthropic field reps who think of Provectus first when they have an implementation need. The second motion is yours to own. You will prospect independently, build relationships, and close deals with enterprise accounts in Financial Services and Life Sciences without a partner assist — operating as a true full-cycle business developer. Responsibilities: Partner motion — Anthropic channel Act as Provectus's primary point of contact with Anthropic's partner and field sales teams. Receive, qualify, and own enterprise leads shared by Anthropic; act as the primary point of contact from first conversation to signed SOW. Identify new co-sell and joint go-to-market opportunities within Anthropic's product and field motion. Maintain a healthy joint pipeline with Anthropic's partner and sales teams; lead quarterly business reviews and co-sell planning sessions. Translate Anthropic's product roadmap and partnership incentives into compelling client propositions. Represent Provectus at Anthropic partner events, executive briefings, and ecosystem calls. Drive partner tier maintenance and upgrade — certifications, co-marketing activations, case study production. New logo hunting Prospect independently into enterprise accounts in target verticals (FSI, Life Sciences) using outbound, networking, events, and referrals. Run the full sales cycle: discovery, solution scoping, proposal, negotiation, close. Build and maintain a personal network of enterprise decision-makers and economic buyers on the East Coast. Cross-functional collaboration Work with Provectus delivery leads and Architects to scope proposals accurately — you are selling consulting engagements, not software licenses. Feed market intelligence — buyer objections, competitive dynamics, vertical patterns — back to leadership and marketing. What You Need to Succeed: 2–3 years of experience in business development, partner/alliance management — with at least part of that in a consulting firm. Proven track record managing an Anthropic, AWS, GCP, Azure or other partner relationship — co-selling, joint pipeline, MDF, or co-marketing. Experience converting partner-sourced leads through a full enterprise sales cycle (discovery to signed SOW). Demonstrated ability to run a full sales cycle independently: prospecting through close, without dedicated BDR support. Experience selling complex, multi-month consulting engagements (statement-of-work deals, not SaaS subscriptions). Excellent executive-level communication skills — written, verbal, and in-room presence at C-suite and VP level. Experience in Financial Services (banking, insurance, capital markets) or Life Sciences (pharma, biotech). Experience in selling AI/ML services, LLM-based products, or cloud data. Willingness to travel (up to 40%) for customer meetings, executive briefings, onsite workshops, conferences, and other business development activities. About Provectus: Provectus is an Artificial Intelligence consultancy and solutions provider, helping businesses achieve their objectives through AI and data-driven innovation organization-wide in such industries as Financial Services, Insurance, Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, and Manufacturing. We are recognized by industry analysts as a leading provider of AI solutions across key business domains. At Provectus, we value innovation, ownership, and collaboration — and we are looking for people who want to grow with us and make an impact. Why Join Us: Work at the intersection of two of the most powerful AI partnerships in the industry — Anthropic and AWS. A world-class AI/ML team that can actually execute on what you sell. Shape how a fast-growing AI consultancy goes to market at a defining moment for enterprise AI adoption. High-impact role with direct visibility to leadership. Strong earning potential with performance-based bonuses. Opportunity to work with cutting-edge AI and cloud solutions. B2B contract model or full-time model. OTE range $120-140k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data. Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan.

Location: Serbia; Spain; Poland; North Macedonia; Armenia; Tbilisi Workplace: remote Provectus is a consulting and professional services firm with a focus on AI/ML based solutions. Provectus is an AWS Premier Partner and an Anthropic partner, helping enterprise clients move from AI experimentation to AI running in production. We are changing how we deliver. Instead of handing a client a design and waiting for someone else to build it, our engineers embed directly inside the client's team and ship the system themselves. We call this Forward Deployed delivery. Before you design anything, you spend real time with the people who do the work the system is meant to change, so the architecture reflects how the work actually happens, not how a requirements document described it. We are looking for a Senior Software Engineer or Solutions Architect with deep Python and Generative AI experience who wants to work this way: deep in the code, close to the client, and directly accountable for whether the system gets used. Direct client communication sits at the center of this role. Prior presales experience is a strong plus. What You Will Do: Embed with the client team for the length of the engagement, working inside their environment rather than alongside it from a distance Spend time with the people who do the job the system is meant to change before you design anything, so the architecture is grounded in how the work actually happens Write clean, production grade Python across AI integrations, backend services, and RESTful APIs (Flask, Django, or FastAPI) Design, build, and optimize RAG systems and agentic AI solutions running in production, not demos or notebooks Own system design and architectural decisions across the engagement: microservices vs monolith, sync vs event driven, SQL vs NoSQL Own the technical direction of the engagement from discovery through delivery Act as the client's direct technical point of contact: present architecture, defend trade offs, and push back on scope when it does not match timeline or budget Support presales activities where relevant, including discovery calls, technical proposals, scoping, and client facing demos Lead architecture reviews, produce technical design documents, and contribute to standards across the Python practice Feed what you learn back into Provectus's blueprint library, so the next engagement starts further ahead Mentor engineers, lead code reviews, and share knowledge across the team What You Will Bring: 7+ years building and running production systems; hands on production experience is required, demo only or POC only backgrounds will not be considered Production experience with RAG systems and LLM based agentic workflows that are live and running, not prototypes Backend development experience with Flask, Django REST, or FastAPI Recent, hands on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered Experience with LLM APIs (OpenAI, Anthropic Claude, or AWS Bedrock) Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization Demonstrated experience making and defending system design and architectural trade off decisions Comfortable owning direct communication with client stakeholders, without a project manager relaying the conversation Genuine willingness to spend time close to the people who do the job before you design a system to change it, and comfort with an engagement that starts underspecified by design Strong testing practices: pytest, mocking, and integration tests for AI systems Experience with Docker and Kubernetes Understanding of LLM evaluation techniques and quality assurance approaches Experience deploying and maintaining AI/ML models in production environments Already using AI assisted development tools in your daily workflow (Claude Code, Copilot, or similar) Proactive and self directed; you own outcomes end to end and spot problems before they are handed to you B2+ English, comfortable collaborating across distributed, multicultural teams Nice to Have: Exposure to Financial Services or Healthcare and Life Sciences, our two primary practice verticals Presales experience: cost estimation, cloud architecture cost optimization, scoped and phased delivery plans Prior consulting, professional services, or other embedded client facing delivery Experience with React or Vue AWS or Claude Code certifications Experience with Streamlit or Gradio for AI prototyping Modern Python tooling (ruff, uv, pyproject.toml, pyright) CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, Node.js, or Rust) What We Offer: Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work

Location: New York, New York; New York City Metropolitan Area; New Jersey; Connecticut; San Francisco Bay Area, California Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name What You’ll Do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice What We Look For: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses) Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production IaC depth: AWS CDK, CloudFormation, Terraform Open-source contributions or public writing on applied AI What We Offer: Full-time employment On-site visits to clients’ facilities and our office in NYC 1/week Unlimited Vacation policy Generous health, vision, and dental insurance 401(K) matching plan Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data No Visa sponsorship How We Hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO

Location: New York; Massachusetts; Washington DC-Baltimore Area; Pennsylvania Workplace: remote About the role: We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name What You’ll Do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice What We Look For: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses) Nice to have: Containers and orchestration (Kubernetes/ECS) and CI/CD in production IaC depth: AWS CDK, CloudFormation, Terraform Open-source contributions or public writing on applied AI What We Offer: Full-time employment On-site visits to clients’ facilities and our office in NYC 1/week Unlimited Vacation policy Generous health, vision, and dental insurance 401(K) matching plan Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data No Visa sponsorship How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO

Location: Spain; Serbia; Poland; Ukraine; Portugal; North Macedonia; Bosnia and Herzegovina; Romania Workplace: remote About Provectus Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.   Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.   Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX, Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for . Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire:   Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant  HR Interview. Soft skills and expectations HM interview. Tech questions; a live engine

Location: Valencia; Poland; Yerevan; Serbia; Kyiv; Madrid; Odesa Workplace: remote About the role: Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. We are hiring an exceptional Senior Solution Owner to sit at the intersection of frontier AI (Claude and agentic systems) and enterprise transformation. You will own the story and the delivery for client engagements built on our Programs (Cowork Activation, Agentic SDLC with Claude Code, and Blueprint Activation) and five Blueprints— packaging reusable IP into repeatable outcomes, and personally getting hands-on in the field when it counts. You are equally comfortable framing an ROI case for a CFO, aligning a healthcare or financial-services stakeholder on a compliant rollout, and pairing with an engineer to wire an MCP integration or ship a Claude Code harness. Domain Focus Deep, current expertise in one or both of our priority verticals is a leading selection criterion: Financial Services (FSI) — e.g., office of the CFO, lending/underwriting, risk, compliance-sensitive workflows. Healthcare & Life Sciences (HCLS) — e.g., revenue cycle management, clinical/operational workflows, regulated data handling. You understand the vocabulary, the buying process, the compliance constraints, and where AI creates defensible value in these industries. Forward-Deployed Delivery (FDE / FDX) Our delivery model pairs a Forward Deployed Engineer (FDE) with a Forward Deployed eXpert (FDX) that lands a Cowork and Blueprint Activation or program inside a client. We normally launch projects in this two-in-the-box model, then extend as the engagement grows. You must be able to credibly play at least one side of that box and partner tightly on the other: FDX — own the domain framing, product definition, rapid-prototyping loop, stakeholder alignment, and OCM; validate use cases through user interviews and turn them into working demos. FDE — configure MCP integrations, build and adapt Claude Code harnesses and skills, wire data pipelines and connectors, and debug in the client environment. Comfort embedding directly with clients and Anthropic field teams, and setting the tone in the first sessions, is essential. Requirements: Deep domain expertise in Financial Services & Insurance and/or HCLS, ideally in a client-facing/consulting context. Proven ability to lead or materially contribute to one of Provectus' Programs or Blueprints (0-to-1 and scale) and land it as real client delivery. Track record operating forward-deployed / embedded with clients (FDE or FDX), including hands-on prototyping. 5-7+ years in solution/product ownership or delivery leadership; 3-5+ years with AI/ML, GenAI, agentic systems, or data platforms. Strong Agile/Scrum experience; familiarity with outcome-based, milestone-priced engagements. Fluent English. A hands-on software engineering background is not strictly required. Working knowledge of Claude, Claude Code, and Cowork, building skills, workflows, and productivity tooling for yourself or your team; MCP integrations, connectors, and custom harnesses are a must. GenAI/agentic patterns: how prompt engineering, RAG, embeddings, vector DBs, and agent frameworks work – well enough to assess quality, challenge assumptions, and translate to client stakeholders. Data fundamentals: what ETL/ELT, data modeling, and governance mean in an enterprise context – well enough to scope integration work and identify data readiness risks. Cloud & AI infrastructure: AWS as the primary platform; what MLOps and AI observability involve – well enough to ask the right questions and understand tradeoffs. Design thinking, data-driven decisions, strong communication and executive storytelling. Bias to action; thrives in ambiguity with structured problem-solving. Enough engineering empathy to earn credibility with senior engineers and architects on day one. Nice to Have: Second priority vertical beyond your primary FSI/HCLS focus. Prior experience in a Premier AWS or Anthropic partner environment. Claude Certified Architect – Foundations (CCA-F), Seller, Developer certification or willingness to complete one early. Certifications: CSPO, SAFe PO/PM, AWS/Azure/GCP. Software development background. What You'll Do: Define value proposition, positioning, and reusable artifacts for your assigned Program (Cowork Activation, Agentic SDLC with Claude Code, or Blueprint Activation) or individual Blueprint; align sales and delivery. Build business cases (market fit, ROI, competitive positioning) and translate them into scoped SOWs. Run market/use-case validation, workshops, and user research; turn findings into demos and first deployments. Stand up Cowork Activation, Agentic SDLC with Claude Code, or Blueprint Activation on live client data; drive rapid prototyping from use case to context to result. Build with Provectus’ delivery stack: Claude Code, AWOS, MCP servers, Skills and plugins. Drive Cowork Activation as a separate, parallel client-facing workstream. Define solution vision and roadmap for GenAI/agentic engagements, RAG, and agentic workflows. Break complex work into incremental releases; balance delivery against technical debt and architecture. Sprint-Enable-Realize engagement model. Lead Agile execution - backlog, sprint planning, release process. Contribute to Provectus' measurement framework that produces the board-level AI Maturity Index, ROI read, and cost signal from the Agentic SDLC program. Define success metrics and analytics; drive continuous improvement and root-cause analysis. Support change management, enablement, and reusable playbooks so wins repeat across accounts. Why Join Us: Deliver frontier work on Provectus' delivery stack — Cowork activation, Agentic SDLC program, and Blueprint Activations across FSI and HCLS — with real client impact. Shape how enterprises in financial services and healthcare adopt AI, from strategy to first deployment. Work forward-deployed in small, senior teams of Forward Deployed Executive + Principal Architect + Forward Deployed Engineers. Grow inside a team actively building the modern AI-delivery practice, tooling, and frameworks. Remote-friendly culture. Private medical insurance or sports coverage Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work.

Location: Yerevan; Poland; Spain; Ukraine; Serbia Workplace: remote About the role: Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. We are hiring an exceptional Senior Solution Owner to sit at the intersection of frontier AI (Claude and agentic systems) and enterprise transformation. You will own the story and the delivery for client engagements built on our Programs (Cowork Activation, Agentic SDLC with Claude Code, and Blueprint Activation) and five Blueprints— packaging reusable IP into repeatable outcomes, and personally getting hands-on in the field when it counts. You are equally comfortable framing an ROI case for a CFO, aligning a healthcare or financial-services stakeholder on a compliant rollout, and pairing with an engineer to wire an MCP integration or ship a Claude Code harness. Domain Focus Deep, current expertise in one or both of our priority verticals is a leading selection criterion: Financial Services (FSI) — e.g., office of the CFO, lending/underwriting, risk, compliance-sensitive workflows. Healthcare & Life Sciences (HCLS) — e.g., revenue cycle management, clinical/operational workflows, regulated data handling. You understand the vocabulary, the buying process, the compliance constraints, and where AI creates defensible value in these industries. Forward-Deployed Delivery (FDE / FDX) Our delivery model pairs a Forward Deployed Engineer (FDE) with a Forward Deployed eXpert (FDX) that lands a Cowork and Blueprint Activation or program inside a client. We normally launch projects in this two-in-the-box model, then extend as the engagement grows. You must be able to credibly play at least one side of that box and partner tightly on the other: FDX — own the domain framing, product definition, rapid-prototyping loop, stakeholder alignment, and OCM; validate use cases through user interviews and turn them into working demos. FDE — configure MCP integrations, build and adapt Claude Code harnesses and skills, wire data pipelines and connectors, and debug in the client environment. Comfort embedding directly with clients and Anthropic field teams, and setting the tone in the first sessions, is essential. Requirements: Deep domain expertise in Financial Services & Insurance and/or HCLS, ideally in a client-facing/consulting context. Proven ability to lead or materially contribute to one of Provectus' Programs or Blueprints (0-to-1 and scale) and land it as real client delivery. Track record operating forward-deployed / embedded with clients (FDE or FDX), including hands-on prototyping. 5-7+ years in solution/product ownership or delivery leadership; 3-5+ years with AI/ML, GenAI, agentic systems, or data platforms. Strong Agile/Scrum experience; familiarity with outcome-based, milestone-priced engagements. Fluent English. A hands-on software engineering background is not strictly required. Working knowledge of Claude, Claude Code, and Cowork, building skills, workflows, and productivity tooling for yourself or your team; MCP integrations, connectors, and custom harnesses are a must. GenAI/agentic patterns: how prompt engineering, RAG, embeddings, vector DBs, and agent frameworks work – well enough to assess quality, challenge assumptions, and translate to client stakeholders. Data fundamentals: what ETL/ELT, data modeling, and governance mean in an enterprise context – well enough to scope integration work and identify data readiness risks. Cloud & AI infrastructure: AWS as the primary platform; what MLOps and AI observability involve – well enough to ask the right questions and understand tradeoffs. Design thinking, data-driven decisions, strong communication and executive storytelling. Bias to action; thrives in ambiguity with structured problem-solving. Enough engineering empathy to earn credibility with senior engineers and architects on day one. Nice to Have: Second priority vertical beyond your primary FSI/HCLS focus. Prior experience in a Premier AWS or Anthropic partner environment. Claude Certified Architect – Foundations (CCA-F), Seller, Developer certification or willingness to complete one early. Certifications: CSPO, SAFe PO/PM, AWS/Azure/GCP. Software development background. What You'll Do: Define value proposition, positioning, and reusable artifacts for your assigned Program (Cowork Activation, Agentic SDLC with Claude Code, or Blueprint Activation) or individual Blueprint; align sales and delivery. Build business cases (market fit, ROI, competitive positioning) and translate them into scoped SOWs. Run market/use-case validation, workshops, and user research; turn findings into demos and first deployments. Stand up Cowork Activation, Agentic SDLC with Claude Code, or Blueprint Activation on live client data; drive rapid prototyping from use case to context to result. Build with Provectus’ delivery stack: Claude Code, AWOS, MCP servers, Skills and plugins. Drive Cowork Activation as a separate, parallel client-facing workstream. Define solution vision and roadmap for GenAI/agentic engagements, RAG, and agentic workflows. Break complex work into incremental releases; balance delivery against technical debt and architecture. Sprint-Enable-Realize engagement model. Lead Agile execution - backlog, sprint planning, release process. Contribute to Provectus' measurement framework that produces the board-level AI Maturity Index, ROI read, and cost signal from the Agentic SDLC program. Define success metrics and analytics; drive continuous improvement and root-cause analysis. Support change management, enablement, and reusable playbooks so wins repeat across accounts. Why Join Us: Deliver frontier work on Provectus' delivery stack — Cowork activation, Agentic SDLC program, and Blueprint Activations across FSI and HCLS — with real client impact. Shape how enterprises in financial services and healthcare adopt AI, from strategy to first deployment. Work forward-deployed in small, senior teams of Forward Deployed Executive + Principal Architect + Forward Deployed Engineers. Grow inside a team actively building the modern AI-delivery practice, tooling, and frameworks. Remote-friendly culture. Private medical insurance or sports coverage Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work.

Location: Tbilisi; Yerevan; Belgrade; Novi Sad, Vojvodina; Poland; Portugal Workplace: remote About Provectus Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits: You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. Requirements: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus What you’ll do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. Nice to Have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire:   Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant  HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible