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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 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: Armenia; Spain; Serbia; Poland; Kyiv City; Kyiv; Odesa; North Macedonia 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: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform. Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably. Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions. Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience. Shape Reddit’s approach to an enterprise-grade RAG system Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform. Own the end-to-end platform strategy from concept through production adoption and long-term evolution. Drive MLOps and LLMOps standards across CI/CD, testing, versioning, evaluation, and lifecycle management. Define best practices for observability, monitoring, governance, and operational excellence across GenAI systems. Partner across engineering, product, and leadership to align platform investments with company priorities and user needs. Champion platform thinking with a strong focus on scalability, reliability, performance, and developer experience. Influence technical direction across teams by turning emerging AI capabilities into a scalable platform strategy. Who You Might Be: 10+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles. Have a track record of leading technical strategy and delivering AI platforms in cloud-based production environments at scale. Demonstrate strong execution by turning strategy into action, driving complex initiatives end to end, and consistently delivering high-quality platform outcomes. Bring deep experience operating Kubernetes and other orchestration systems in large-scale production environments. Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc. Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders Strong focus on scalability, reliability, performance, and developer experience. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle. Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $292,500 — $409,500 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: London Workplace: OnSite About Clarity We’re pioneering Agentic AI — systems that don’t just respond, but reason, act, and adapt autonomously in complex workflows. This is about crafting AI Agent Experiences — designing agents that collaborate seamlessly with humans, learn from context, and make every customer interaction faster, smarter, and more empathetic. You’ll own the technical vision and turn requirements into a live, reliable product used by brands like Grubhub, Booking.com http://Booking.com, Dropbox, Uber, Careem, and Fubo. You’ll collaborate directly with engineers, other tech leads, directors, and the CTO to evolve ambitious prototypes into a rock‑solid, scalable platform What you’ll actually do 50% Build — design & ship - Agentic AI for CX: Real‑time assistants that listen to calls/chats, retrieve from customer KBs, and draft responses with human‑in‑the‑loop controls. - Structured extraction: Schema‑driven pipelines over unstructured text (and other modalities) using retrieval, tool‑use, and robust LLM prompting. - Hybrid anomaly detection: Blend classical time‑series methods (e.g., decomposition, change‑point, forecasting) with LLM‑aware, contextful detectors for seasonality, spikes, step‑changes, and drift. - Novelty discovery: Embedding‑based clustering and drift, topic surfacing, LLM summarization of emerging themes with deduplication and evidence links. - Alerting & scoring: Severity/impact ranking, de‑noising, suppression/cool‑downs, routing, and feedback loops. 25% Architect & scale - Own reliability, latency, and cost. Design online/offline eval harnesses, canaries, and SLAs; operate GPUs/accelerators where needed. - Stand up and harden RAG pipelines (indexing, retrieval policies, grounding, guardrails) and agent frameworks. - Take basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost tuning. - Participate in on‑call for your area and drive root‑cause analysis with crisp follow‑ups. 15% Collaborate - Pair with back‑end & front‑end to wire extractors/detectors and agents into ticketing, voice, and analytics stacks (APIs, webhooks, real‑time streams). - Partner with PMs/CX to evolve taxonomies, schemas, and guardrails; translate business problems into shipped ML features. 10% Align & showcase - Gather requirements from CX and product leads, demo new capabilities to execs & customers, and document impact with precision/recall, alert quality, latency, and cost metrics. What makes you a great fit - Startup hacker mindset: You self‑start from zero, respect no silos, and carry work from prototype to production. 🛠️ - AI‑native dev tools are your daily drivers: Cursor, v0, Claude Code (or similar). - 7–10 years building production ML/back‑end systems; 2+ years leading while coding. - Expert Python; strong back‑end chops (e.g., FastAPI, gRPC, Postgres, pub/sub/streams). - Agents & RAG: Fluency with at least one agent framework (ADK preferred). Proven track record shipping AI agents and building RAG pipelines. - LLM + DS depth: Prompting/tooling, retrieval design, LLM evals; hands‑on with time‑series analysis (forecasting, change‑point, drift). - Cloud & ops: Basic infra ownership on GCP (or AWS/Azure): networking, autoscaling, CI/CD, IaC, observability, and cost control. - Communication: You explain results clearly, align stakeholders, and write crisp docs. Bonus points - DevOps wizardry; GPU/accelerator experience. - Multimodal pipelines (text + voice + screenshots). - Prior experience in contact center/CX analytics or novelty/anomaly systems. - Founder or founding engineer experience

Location: United States Workplace: Remote Coder is looking for a Senior Account Executive to grow our diverse customer base. You’ll help bring Coder’s platform to some of the largest companies in the world, who are focused on executing AI-centric software development at scale. This role is about building trusted relationships, shaping deals, and making sure enterprise customers clearly see the value we deliver. Day to day, you will manage the full sales cycle, from sourcing opportunities to closing contracts. You’ll work side by side with engineers, buyers, and internal partners to remove friction and move complex deals forward.   What you’ll do here - Build and close a strong pipeline of enterprise accounts with large engineering organizations - Generate qualified opportunities through outbound prospecting and inbound leads - Lead compelling demos that differentiate Coder, and communicate our value with clarity and conviction - Collaborate with Sales Engineers to deliver a thorough technical evaluation - Partner with decision-makers and technical stakeholders throughout the sales cycle - Travel as needed to support deals and customer relationships   What we’re looking for - 5+ years in software sales with a strong prospecting background (ideally Developer, Agent, DevSecOps, or Cloud Native Computing Foundation (CNCF) technologies) - 3+ years selling into Fortune 500 companies - Experience engaging with software engineering leaders and technical decision-makers - Understanding of DevOps, CI/CD, platform engineering, and developer tools - Experience with GenAI & Agentic development tools (Cursor, Claude, Windsurf, Goose, Copilot, etc) - Comfortable with outbound motion and partnering with Sales Engineers - Track record of exceeding quota and pipeline goals - Strong communication skills - written, verbal, and in presentations - Familiarity with different sales cycles (startup, midsize, enterprise) - Creative, analytical, and highly self-motivated - Ability to travel up to 15%   Bonus tacos if you have - (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) - A technical background or meaningful experience with open source software - Curiosity about emerging AI workflows, developer tools, and general tech trends ABOUT CODER Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com. INTERVIEW PROCESS  We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders. AI USE DURING THE INTERVIEW PROCESS As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process. Not permitted: Using AI assistance during conversational interviews. Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly. OUR USE OF AI IN HIRING We use AI tools to help manage our recruitment process efficiently and fairly. Specifically: - Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first. - Granola takes notes during our interview calls so our team can focus on the conversation with you. All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models. In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf. If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.   CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.

Location: Intellias Meet your recruiter Daniela Riabova daniela.riabova@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering GenAI Engineer Senior Poland Remote APPLY NOW REFER A FRIEND A leading German distributor of building materials, the company serves construction professionals and private customers through an extensive network of branches and showrooms. It offers a comprehensive range of products and services for residential construction and renovation, providing a convenient one-stop shop for its customers. What project we have for you For an innovative AI project in the retail sector, we are seeking an experienced AI Engineer (m/f/d) to support the development and implementation of an AI-powered pricing model. The aim of the project is to link internal and external data sources and, using machine learning and neural networks, generate dynamic, AI-based price recommendations for individual items. This is intended to optimise pricing decisions and unlock additional margin potential. The technological foundation is a prototype that has already been successfully developed and implemented by international colleagues in collaboration with Microsoft. The existing solution is to be transferred to the company’s own data environment, adapted and further developed. The data model, as well as existing Python code and notebooks within Azure Databricks, are already in place. Working alongside the in-house data science team, you will be responsible for developing, training and validating a proprietary AI model based on these resources. As the project progresses, the solution will be integrated with the ERP system to provide automated price and terms suggestions for operational staff. What you will do • Further development and customisation of an existing AI pricing prototype based on Azure Databricks • Analysis and processing of internal and external data sources • Development and implementation of neural networks and machine learning models • Development, training and validation of proprietary AI models • Implementation and optimisation of AI models using Python • Use and processing of Large Language Models (LLMs) and prompt engineering • Porting existing models to the company’s own data and system landscape • Collaboration with the internal data science team and international project stakeholders • Supporting the integration of the developed solution into the existing ERP system What you need for this At least 2–3 years’ practical project experience in AI engineering or similar AI projects • Very good knowledge of Azure Databricks • Very good knowledge of Python • Substantial experience in machine learning and deep learning • Practical experience in the development, training and validation of neural networks • Experience working with Large Language Models (LLMs) and prompt engineering • Experience in the development and implementation of AI models in real-world business environments • Ability to translate business requirements into technical models and solutions • An independent and structured approach to work, as well as good communication skills • knowledge of German required (B1/B2) • Occasional on-site attendance in Dortmund (approx. 2–3 appointments per quarter) Nice-to-have: • Experience in the retail sector • Experience with pricing models and predictive analytics • Experience integrating AI solutions into ERP systems What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Workplace: Москва и Краснодар (гибрид/офис), другие города - удаленно Ищем Fullstack разработчика (PHP + Vue3) для проекта "Пульс Магнит" - это масштабная платформа, создающая единое информационное пространство для взаимодействия компании с подрядчиками, арендодателями, франчайзи и внутренними службами. Проект направлен на полную цифровизацию процессов эксплуатации торговых точек, ремонта оборудования и развития сети, объединяя разрозненные задачи в эффективную систему управления. Основу проекта составляет веб-платформа личных кабинетов, предназначенная для всех категорий внешних и внутренних пользователей. Здесь реализованы сложные интеграционные потоки, механизмы парсинга данных и инструменты для управления жизненным циклом сотрудничества. Команда: руководитель, 2 бекенд-разработчика (РНР), 1 фронтенд-разработчик (Vue3), 1 UX/UI дизайнер, системный аналитик. Стек технологий: PHP8, JS, TS, Laravel, Vue3, Cloud Native, PostgreSQL, Kafka, Redis, S3, Git, Podman. Задачи Разрабатывать и поддерживать сервисы личных кабинетов в экосистеме «Пульс»: микросервисы бэкенда и веб-интерфейсы для внешних и внутренних пользователей Проектировать и разрабатывать интеграции с корпоративными системами Принимать и документировать архитектурные решения: стек, структура репозиториев, паттерны взаимодействия микросервисов (совместно с архитектором и руководителем) Проводить code review, менторить бэкенд- и фронтенд-разработчиков команды, развивать стандарты разработки, внедрять AI-инструменты в процесс разработки и покрывать функционал автоматическими тестами; разрабатывать CI/CD и конвейера поставки (совместно с devops-инженером) Взаимодействовать со смежными командами по техническим требованиям и срокам Заниматься эксплуатацией и развитием сервисов после запуска: производительность, надёжность, доработки по результатам эксплуатации Требования Опыт коммерческой разработки на PHP с применением реактивных фреймворков на фронтенде от 5 лет; из которых хотя бы 2 года на PHP8 и Vue3 От года опыта на позиции техлида, сеньора, тимлида Глубокое понимание Cloud Native, реляционных и нереляционных СУБД, асинхронного программирования Опыт работы с микрофронтендовой и микросервисной архитектурой Опыт в энтерпрайз-разработке Понимание требований информационной безопасности Уверенное владение ИИ-инструментами Условия Трудоустройство в аккредитованную IT‑компанию ДМС со стоматологией и льготными условиями для членов семьи Работу в уютном офисе в центре Москвы (ст. м. Савеловская), Краснодаре и удаленную работу в других регионах РФ Корпоративные скидки PRIMEZONE, бесплатная подписка Магнит Премиум с повышенным кешбэком по программе лояльности М+ Поддержку в развитии через обучение, конференции и митапы, а также программу для руководителей - Leadership club IT‑комьюнити - среда, где быстрее находишь решения, делишься практиками, пробуешь новые роли и растешь от эксперта в стекe до лидера инициатив Мы являемся партнером Минцифры России по проекту Национальная система подтверждения IT‑компетенций Работа над масштабными продуктами и проектами (Умный магазин, роботизация, беспилотность, GenAI и другое) Социально– психологическая поддержка от >370 специалистов по направлениям: юристы, психологи, врачи, финансовые и ЗОЖ советники Формат работы Москва и Краснодар (гибрид/офис), другие города - удаленно

Responsibilities: — Own the commercial relationship and customer strategy across a large customer base in EMEA. — Retain and grow existing customers by building trusted relationships. — Identify high-value opportunities for deeper engagement. — Serve as a strategic point of contact for cloud-provider teams supporting customer growth. The role is remote and open to candidates located in the Netherlands, Estonia, Sweden, and Spain. About the company: DoiT is a global technology company specializing in cloud-driven business growth and innovation. They combine data, technology, and human expertise to help customers operate in a well-architected and scalable state from planning to production. Their solution, DoiT Cloud Intelligence, integrates advanced technology with human intelligence to solve complex multicloud problems and drive efficiency. They have expertise in Kubernetes, GenAI, CloudOps, and more, and are strategic partners of AWS, Google Cloud, and Microsoft Azure, serving over 4,000 customers worldwide.

Location: Воронеж Наша команда занимается сопровождением Интеллектуальной системы управления, которая позволяет повысить эффективность руководителей и сотрудников Сбера за счёт автоматизации процессов, внедрения AI-помощников и GenAI для принятия лучших решений и развития подчиненных. Обязанности * администрирование и поддержка Linux-инфраструктуры * диагностика инцидентов и поиск корневых причин сбоев * мониторинг производительности систем и обеспечение их стабильной работы * взаимодействие с командами разработки для решения технических задач * участие в процессах по повышению отказоустойчивости сервисов. Требования * опыт работы с системами мониторинга (Zabbix, Grafana, Prometheus, Victoria Metrics) от 2-х лет * знание методологий SRE и опыт работы с контейнеризацией (K8s, OpenShift). * понимание процессов информационной безопасности (SSL, mTLS, работа с сертификатами) * опыт с инструментами логирования и обмена сообщениями (ELK, Kafka) * практический опыт с инструментами DevOps (Git, Jenkins, Nexus, BitBucket) * навыки автоматизации задач и программирования (Bash, Python), базовые знания SQL. Условия * работа в удобном и современном офисе в г. Воронеж, улица 9 Января * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка СберПрайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Москва Наш продукт — это ИИ-помощник, который разработан для помощи сейлзам и трейдерам, снимая с них часть рутинных задач и процессов. Обязанности * тестирование качества ответов AI-навыков: релевантность, полнота, корректность, отсутствие галлюцинаций и «уверенных, но неверных» ответов * формирование и поддержка эталонных датасетов (golden set) для регрессионной оценки LLM-ответов и промптов * тестирование промптов, RAG-конвейеров и маршрутизации оркестратора — правильный ли агент/навык выбирается под запрос, полные ли источники подтягиваются * оценка недетерминированного поведения: прогон запросов N раз, статистические метрики стабильности и качества, выявление регрессов качества между версиями моделей/промптов * разработка, ревью и поддержка тест-кейсов, чек-листов, тест-планов * взаимодействие с разработчиками, аналитиками, DS/ML-инженерами и PO для уточнения требований * ведение баг-трекинга в Jira, документирование в Confluence. Требования * опыт в роли QA от 3 лет * опыт функционального и сквозного (E2E) тестирования * опыт тестирования API и интеграций: REST/gRPC, форматы запросов/ответов, работа с моками внешних сервисов * умение составлять и проверять тест-кейсы в Zephyr, анализировать покрытие * понимание принципов работы LLM и GenAI: промпты, RAG, температура/вариативность, ограничения моделей, типовые режимы отказа (галлюцинации, потеря контекста, неверная интерпретация запроса) * опыт оценки качества AI-ответов: эталонные наборы, ручная и полуавтоматическая разметка, метрики точности/полноты/faithfulness/relevancy * навыки написания скриптов на Python для прогона батчей запросов, сбора и сравнения результатов. ### Будет плюсом: * опыт в финтехе / банковской сфере * опыт тестирования AI/ML-продуктов: чат-боты, ассистенты, рекомендательные системы * знание инструментов оценки LLM: LangSmith, DeepEval, Arize, RAGAS или аналоги * базовые знания автоматизации тестирования (Java, Python). * опыт работы с системами мониторинга (Grafana), включая мониторинг качества AI-ответов * понимание требований комплаенса и работы с чувствительными данными. Условия * комфортный современный офис на Вавилова, 19 * формат работы – гибрид * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Location: London Workplace: Remote Coder is looking for a Senior Sales Development Representative (SDR) to fuel our growth by generating qualified pipeline for our Enterprise Account Managers. You’ll help bring Coder’s Environment-as-a-Service platform to some of the world’s largest companies that are adopting AI-driven development at scale. This role is all about creating opportunities: finding and engaging the right prospects, uncovering the pain points Coder can help with, and setting up qualification calls that set our EAMs up for success. You’ll play a critical role in driving Coder’s outbound motion and helping large organizations build software faster, more securely, and at scale through the collaboration of AI coding agents and human developers.   What you’ll do here - Generate qualified opportunities for EAMs through targeted outbound prospecting - Conduct multi-channel outreach across phone, email, and LinkedIn using tools like SalesLoft, Sales Navigator, ZoomInfo, 6sense, and Nooks - Research target accounts and key personas to craft personalized and value-driven messaging - Set up qualification calls for EAMs to run and advance through the sales cycle - Work closely with EAMs to strategize account outreach and hand off qualified opportunities seamlessly - Maintain accurate activity and lead data in CRM and engagement platforms - Collaborate with marketing to align messaging and campaigns to drive higher response rates - Stay sharp on developer tooling, platform engineering, and AI-driven development trends to speak credibly with prospects   What we’re looking for - 1-3 years in outbound SDR or BDR roles within SaaS or developer-focused technology companies - Proven ability to generate pipeline through outbound cold calling, emailing, and social selling - Experience with SalesLoft, LinkedIn Sales Navigator, ZoomInfo, 6sense, and similar prospecting tools - Strong written and verbal communication skills; able to clearly articulate technical value propositions - Grit, curiosity, and the ability to handle rejection while maintaining a positive, proactive mindset - Highly organized and self-motivated with a focus on measurable goals and continuous improvement - Eagerness to learn about developer tools, DevOps, platform engineering, and AI workflows   Bonus tacos if you have - (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) - Prior experience selling into engineering or DevOps personas - Familiarity with AI and GenAI developer tools - Knowledge of open source ecosystems or cloud-native technologies - Experience collaborating closely with Account Executives in an enterprise sales motion ABOUT CODER Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com. INTERVIEW PROCESS  We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders. AI USE DURING THE INTERVIEW PROCESS As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process. Not permitted: Using AI assistance during conversational interviews. Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly. OUR USE OF AI IN HIRING We use AI tools to help manage our recruitment process efficiently and fairly. Specifically: - Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first. - Granola takes notes during our interview calls so our team can focus on the conversation with you. All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models. In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf. If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.   CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.

Задачи: — Развивать методологию финансовой оценки бизнес-инициатив всех направлений бизнеса Группы и превращать её в инструменты для AI-агента. — Проводить аналитику и разрабатывать методологию финансовой оценки. — Проектировать алгоритмы сбора, обработки и анализа данных и реализовывать их на SQL, Python, Pyspark. — Превращать алгоритмы в полноценные инструменты для AI-агента. — Описывать бизнес-требования для автоматизации на внутренних платформах. — Сопровождать разработчиков в процессе автоматизации. — Проверять и принимать готовые решения. — Отвечать за прохождение идеи от методологии и прототипа до работающего инструмента для AI-агента. Требования: — Высшее образование в области экономики, финансов, математики или физики. — Знание экономики и корпоративных финансов. — Знание математической статистики, эконометрики, понимание принципов A/B-тестирования и альтернативных методов оценки эффектов. — Уверенное владение SQL и Python, опыт работы со Spark будет плюсом. — Знание английского языка. — Навыки работы с GenAI решениями. — Опыт работы в сфере финансов, рисков или анализа данных от 0 до 5 лет (junior и middle). — Личностные качества: самостоятельность, системное и критическое мышление, структурность, коммуникабельность, исследовательский интерес, целеустремлённость, умение доводить дело до конца. Условия: — Полная занятость. — Конкурентная заработная плата (финальное значение определяется по итогам собеседований). — ДМС, корпоративное обучение, фитнес. — Перспективы карьерного роста.

Location: Intellias Meet your recruiter Stephen Palmer stephen.palmer@intellias.com https://www.linkedin.com... Vacancy details Management Manager Director Bulgaria, Croatia, Poland, Portugal, Spain, United Kingdom Remote APPLY NOW REFER A FRIEND Over 20 years of market experience, Intellias brings together technologists, creators and innovators in Europe, North and Latin America, and the Middle East. Join our international team and take the mission to solve the advanced tech challenges of tomorrow! What project we have for you We are building a market-leading AI Solutions practice and are looking for a senior leader to anchor it across Europe. This is a hands-on leadership role at the intersection of technical depth, client advisory, and commercial growth. You will work with business segments and co-own AI outcomes end to end — from shaping opportunities and advising client executives, through architecting and delivering production-grade solutions, to building the team and offerings that let us scale. This is not a pure management role and not a pure architect role. The right person can sit with a client CTO in the morning to frame a transformation roadmap, dive into a model architecture or agent design review in the afternoon, and shape the next quarter’s offering and pipeline in between. You will be a founding pillar of how we take AI from pilot to production at enterprise scale. What you will do Client Advisory & Pre-Sales Act as the senior AI advisor and trusted partner to enterprise clients, translating business problems into pragmatic, value-driven AI strategies and roadmaps. Lead pre-sales and solutioning: shape opportunities, scope and estimate engagements, run discovery and design workshops, and present to senior and C-level stakeholders. Drive proposal and RFP responses, solution narratives, and commercial framing that differentiate us in competitive situations. Identify and grow account opportunities, partnering with business development to convert advisory engagements into delivery programs. Offering & Practice Development Define and productize repeatable AI offerings, accelerators, and reusable assets that shorten time-to-value and improve delivery margins. Establish reference architectures, delivery playbooks, and engineering standards for ML, GenAI, and agentic solutions. Contribute to AI practice strategy and external thought leadership (points of view, frameworks, speaking, content). Delivery Leadership Support end-to-end delivery of AI programs — from PoC and pilot through to hardened production — ensuring solutions actually ship and operate, not just demonstrate. Drive production readiness across the lifecycle: MLOps/LLMOps, evaluation, monitoring, cost management, security, and AI governance. Manage program economics, scope, risk, quality, and stakeholder alignment across distributed delivery teams. Technical Leadership Provide hands-on technical direction across machine learning, deep learning, and GenAI/agentic systems, with the credibility to lead architecture and design reviews. Make and defend platform and architecture decisions across hyperscaler and data ecosystems (AWS, Azure, GCP, Databricks, Salesforce etc.). Set technical standards and uphold engineering quality, mentoring senior technical staff. Team Building & Leadership Recruit, build, and grow a high-performing AI delivery organization in Europe across data science, ML/AI engineering, and solution architecture. Manage, coach, and develop senior practitioners; foster a culture of capability growth, certification, and continuous learning. Operate effectively within a collaborative leadership model alongside business development and technology peers. What you need for this 12+ years in technology, data, or engineering, with strong hands-on background in AI / ML / data science, including genuine hands-on practice (not solely oversight). Demonstrable hands-on expertise in machine learning and deep learning— model development and experimentation with frameworks such as PyTorch or TensorFlow, and a working command of modern ML/DL techniques. Proven track record delivering AI/ML solutions into production at enterprise scale — you have shipped systems that operate reliably in the real world. Production experience on at least one major hyperscaler or data platform(AWS, Azure, GCP, or Databricks); multi-platform fluency is a strong advantage. Hands-on production experience with GenAI and agentic systems — LLMs, RAG, orchestration and agent frameworks, tool/function calling, and evaluation of non-deterministic systems. Experience leading both internally and externally — line-managing internal teams and owning external client programs as a delivery lead, engagement lead, or equivalent accountable role. Executive-grade client presence — able to advise, influence, and build credibility with senior business and technology stakeholders. Nice to Have: Prior consulting or IT/professional-services experience — pre-sales, offering development, and accountability for running AI projects and programs (including revenue or margin contribution). Experience building or scaling an AI / data practice or capability from an early stage. Deep domain expertise in one or more priority verticals — e.g., retail, automotive & mobility, financial services, healthcare / medtech & life sciences, or telecom — sufficient to speak the client’s language and frame value, not just technology. Familiarity with EU AI Act, GDPR, and responsible-AI / governance frameworks as applied to enterprise deployments. Relevant certifications (AWS / Azure / GCP ML or AI, Databricks). Advanced degree (MSc or PhD) in Computer Science, Data Science, Machine Learning, Engineering, or a related field. Experience operating within nearshore / distributed delivery models. Additional European languages. What Success Looks Like (First 6–12 Months) Established credibility with key clients and internal stakeholders as the go-to senior AI leader for one or more business segments. Shaped and helped win AI engagements, with a measurable contribution to pipeline and bookings. Stood up or sharpened a set of productized AI offerings and accelerators that the team can sell and deliver repeatably. Promoted delivery and engineering standards and begun building a growing, high-quality AI team with measurable impact Delivered (or put firmly on track) at least one flagship AI program running in client production. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Intellias Meet your recruiter Olha Huk olha.huk@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering GenAI Engineer Senior Romania Hybrid APPLY NOW REFER A FRIEND Intellias helps retailers deliver consistent, omnichannel experiences through technology. Join us to develop scalable solutions that drive performance and customer value What project we have for you We are looking for a hands-on Senior AI Engineer to lead the technical design and delivery of enterprise AI agents and MCP-based integrations. The team will develop Model Context Protocol (MCP) services for local business applications and build AI agents that consume both these local MCPs and MCP services provided by a global platform team. The Senior AI Engineer will own solution design, support use-case discovery, provide technical leadership to the engineering team, and participate directly in implementation. What you will do Lead technical discovery and translate business use cases into AI/agentic solution designs. Design the architecture of AI agents and their interaction with local and global MCP services. Design and develop MCP services exposing capabilities of local applications to AI agents. Build enterprise AI agents and agentic workflows. Integrate agents with multiple MCP servers, APIs and enterprise systems. Define agent instructions, reasoning flows, tool-selection logic, approval workflows and human-in-the-loop guardrails. Define reusable patterns and engineering standards for MCP and agent development. Lead and support other AI engineers during implementation. Ensure compliance with enterprise security, architecture and AI governance requirements. Define and monitor agent quality and performance metrics, including task completion, tool failures, hallucinations, latency and cost. Collaborate with global AI/platform teams to ensure interoperability between local and global MCP capabilities. What you need for this Required skills Strong hands-on Python engineering experience. Experience building LLM-based applications, AI agents or agentic workflows . Strong knowledge of REST APIs and enterprise integrations. Strong Microsoft Azure experience. Experience with authentication/authorization such as OAuth 2.0 and Microsoft Entra ID. Understanding of tool/function calling and agent-to-system integration patterns. SQL, JSON, Git and CI/CD. Ability to design production-grade solutions and provide technical leadership. Strong English communication skills. Strong advantage Hands-on Model Context Protocol (MCP) experience. Azure AI Foundry / Azure OpenAI. Copilot Studio. Power Automate. Agent orchestration frameworks such as Semantic Kernel, LangGraph or similar. Azure Functions / API Management / Logic Apps. Experience with enterprise AI governance, evaluation and observability. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: Denver, CO, United States About Us Fanatics is a leading global sports platform redefining how fans connect with the teams, players and moments they love. Our businesses — Fanatics Commerce, Fanatics Collectibles, Fanatics Betting & Gaming, Fanatics Events, Fanatics Advertising, Fanatics Markets and Fanatics Studios — maximize the presence and reach for hundreds of partners globally and create a one-stop experience that allows fans to buy, bet, collect, and earn, while engaging with sports in deeper, more immersive ways. This includes licensed fan gear and lifestyle products, sportsbook and iGaming, physical and digital trading cards, live events, premium sports entertainment content, credit card offerings and more. Together, they form a powerful, integrated ecosystem — connected by the Fanatics ONE loyalty program and FanCash, the currency of sport — delivering personalized experiences to over 100 million fans worldwide. Fanatics holds partnerships with over 900 sports properties, from professional leagues and players’ associations to teams, colleges and retail partners; over 7,000 athletes and celebrities; and over 2,000 retail locations, including all Lids stores. Backed by a team of more than 22,000 employees, Fanatics is committed to relentlessly enhancing the fan experience. About the Team Launched in 2021, Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. The Fanatics Sportsbook is available to 95% of the addressable online sports bettor market in the U.S. Fanatics Casino is currently available online in Michigan, New Jersey, Pennsylvania and West Virginia. Fanatics Betting and Gaming operates twenty-two retail sports betting locations, including the only sportsbook inside an NFL stadium at Northwest Stadium. Fanatics Betting and Gaming is headquartered in New York with offices in Denver, Leeds and Dublin. Overview Fanatics Betting & Gaming is continuing to build and evolve AI-powered customer experiences through our GenAI customer service chatbot (FBGA) and our internal co-pilot for customer service agents, ARENA. The quality of those experiences depends on the knowledge behind them. As Senior Manager, Knowledge Management, you will lead the team that owns that knowledge base, turning what we learn from customer cases into the best user experience possible, whether for our end customers or internal stakeholders. You will work with automated tooling developed by our Engineers to build and refine knowledge articles (KAs), drawing on input from stakeholders, operational data from our customer contacts, and signals from our evaluation and quality data. You’ll be Operations’ primary partner to Product and Engineering on knowledge, content, and the systems that deliver it. This role suits an exceptionally organized leader who can run a disciplined content lifecycle, translate case data into prioritized action, and operate comfortably from strategy through execution.This role suits an exceptionally organized leader who can run a disciplined content lifecycle, translate case data into prioritized action, and operate comfortably from strategy through execution. Responsibilities Knowledge base ownership Own the knowledge base that powers FBGA and ARENA, including its structure, taxonomy, content, accuracy, and coverage Establish and run a content lifecycle with clear owners, testing and review cadences, and approval workflows, so content stays current as policies, products, and states change Set and enforce content standards that keep knowledge consistent, compliant, and easy for both people and AI to use Drive the evolution of internally developed tools and automated processes so that Knowledge can scale and keep pace with the broader business Insights and trend analysis Drive analysis of trends across case types and subtypes, focusing on containment, escalation, repeat contact, and delivering a quality user experience. Turn trends and quality findings into a prioritized backlog of content, process, and product improvements, and see them through to impact Deliver regular readouts to Operations leadership and partner teams that connect knowledge changes to measurable outcomes Cross-functional partnership Serve as the Operations lead partner to Product and Engineering on knowledge systems, tooling, and the requirements that shape how knowledge reaches FBGA and ARENA. Partner with our Quality team to act on evaluation findings, and with our Go-To-Market team so launch content is ready before go-live Surface customer and operational insights to Product, Marketing, Compliance, and other frontline teams Team leadership Lead, hire, and develop the Knowledge team, setting clear priorities and raising the bar on rigor and ownership Build the operating rhythm for the team, including planning, intake, prioritization, and reporting, so work is visible, organized, and predictable Ensure the team follows all internal and external guidelines and regulations. Qualifications 8+ years of experience in operations, knowledge management, customer experience, or a related field, including leading teams. Proven ability to build and run a content or knowledge function with defined standards, ownership, and governance. Strong analytical skills, with the ability to synthesize large amounts of case and performance data into clear priorities and recommendations. Track record of partnering effectively with Product and Engineering teams on requirements, prioritization, and delivery. Rigorous attention to detail and strong organization, with the ability to manage many parallel workstreams and deadlines. Exceptional written and verbal communication, including the ability to tell a clear, data-backed story to senior leaders. Ability to operate from strategy to execution, and to turn strategy into operating practice. Ability to pass required licensing mandated by state racing and gaming regulatory bodies. Bachelor’s degree or equivalent experience. Preferred Qualifications Experience with AI-assisted support, chatbots, or retrieval-based knowledge systems, and how content quality affects their performance. Experience in online sportsbook, casino, or poker, or another regulated, fast-moving environment. Familiarity with proprietary online gaming tools, systems, and reports (Fraud, Payments, Gaming, Sportsbook). Experience with knowledge management platforms and content analytics. Hands-on SQL or data analysis skills. Deep empathy for the customer and curiosity about technology as a customer experience enabler. Master’s degree Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE—a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process. For information about our benefits, please visit https://benefitsatfanatics.com/ Ranges will change based on country and state of residence, which are reflected in Geographical Zones defined by Fanatics Betting and Gaming. The range incorporates all of our Geographical Compensation Zones and is subject to change as the Zone associated with the actual offer is confirmed. In addition to the base and bonus, full-time employment, and more. For information about our benefits, please visit https://benefitsatfanatics.com/ Salary Range $150,000 — $170,000 USD By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy. Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here .

About the Role This is a hands-on engineering position combining software development, solution design, prototyping, and direct customer interaction. You will work closely with enterprise customers to understand their operational processes, existing systems, technical constraints, and business pain points — and then help translate those needs into practical technical solutions. The role is ideal for someone who is technically strong but also comfortable working directly with business and technical stakeholders. What You Will Do — Work directly with enterprise customers to understand workflows, systems, and pain points — Gather and clarify requirements with business and technical stakeholders — Translate ambiguous business needs into technical solutions — Build prototypes, integrations, and production-ready functionality — Design and implement APIs and system integrations — Work with databases and data integration flows — Support cloud-based solution design and implementation — Explain technical decisions, trade-offs, and architecture clearly to customers — Collaborate with internal engineering and delivery teams — Take ownership of solutions from initial discovery through implementation — Participate in customer meetings and occasional business trips to Paris MUST HAVE — Strong software engineering / programming background — Hands-on experience building production systems — Experience with APIs and system integrations — Strong understanding of databases and data integration — Experience with cloud platforms and services — Ability to prototype and implement solutions quickly — Strong problem-solving skills and ability to work with incomplete or evolving requirements — Excellent customer-facing communication skills — Confidence working with both technical and non-technical stakeholders — Ability to ask the right questions and explain technical concepts clearly — Availability for occasional business travel to Paris Nice to Have — AI / Machine Learning experience — LLM-based applications — AI Agents / Agentic workflows — RAG or GenAI integrations — Experience in consulting, solutions engineering, technical presales, or customer-facing engineering — Enterprise integration or digital transformation projects What We’re Looking For We are looking for someone who is not only a strong engineer, but also comfortable being close to the customer. You should enjoy understanding how a business actually works, identifying what needs to be improved, and turning that understanding into a practical technical solution. Conditions — Location: EU — Business travel: occasional trips to Paris, fully covered by the company What We Offer — Small-company feel within a fast-growing international environment — Friendly, collaborative, and mission-driven team — Fully paid business trips to Paris — 25 calendar days of vacation + 5 additional paid sick days — Medical insurance — Corporate English courses — Corporate events and team-building activities — Support with professional certifications — Reimbursement for professional courses and training — Long-term international projects — Opportunities for professional and technical growth