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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: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are looking for a Staff AI Engineer to join the GenAI + Discovery Platform team at Strava, a team at the core of Strava's AI strategy, responsible for building the shared tooling that enables product teams to ship high value GenAI-powered features at scale. This role sits at the intersection of AI engineering, platform engineering, and server engineering. You will own the systems that make it easy and reliable for all of our product teams to build user facing features on top LLMs at Strava, from shared context, tool management, agent loops, orchestration, data access, search and retrieval to evaluation and ROI frameworks. This is a high-leverage technical role: you're not just building infrastructure, you're building the core understanding of athletes that enable consistent athlete experiences, insight across product surfaces. You'll work closely with product engineers, product managers and data teams to translate cutting-edge AI capabilities into production-ready platforms that facilitate development of AI features that provide value to our athletes. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office — three days per week. WHAT YOU'LL DO: - Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide. - Build the GenAI + Discovery Platform: Set the vision, Design and the shared genAI platform: LLM, and workflow orchestration, prompt management systems, RAG pipelines, search and retrieval services (vector, hybrid and structured search), and evaluation tooling - Enable Teams to Ship AI Features Faster: Build self-serve interfaces and golden paths so that product and CUJ engineering teams can build GenAI-powered features without deep AI expertise. - Own End-to-End AI Capability Delivery: Drive projects from architecture and interface design through production deployment and monitoring, ensuring correctness, latency, reliability, and cost-efficiency of the AI capabilities your platform serves. - Collaborate Across Engineering, and Product: Work closely with engineers and PMs across different verticals to enable the new features and build the genAI roadmap. inform product teams on how to consume and leverage AI capabilities effectively. - Build from a Rich Dataset: Explore and use Strava's extensive unique fitness and geo datasets from millions of users to inform how AI capabilities can extract actionable insights, improve product decisions, and power novel athlete experiences. YOU WILL BE SUCCESSFUL HERE BY: - Treating AI Platform as a Product: Bringing engineering rigor — versioning, contracts, SLAs, monitoring, and deprecation paths — to AI capabilities and LLM integrations that product teams depend on. You don't ship a prototype; you ship a platform. - Leading as an Owner: Taking end-to-end accountability for the reliability and impact of the systems you build, including their correctness in production, their adoption by downstream teams, and the business outcomes they enable. - Building for Leverage: Designing platforms and tooling that multiply the output of the broader team, reducing the AI infrastructure expertise required for CUJ teams to ship GenAI-powered features. - Collaborating Across Disciplines: Working fluidly with ML engineers, data engineers, data scientists, and product managers to align on model selection, evaluation standards, prompt strategies, and consumption patterns. - Raising the Standard: Helping establish best practices for GenAI system development, responsible AI patterns, and operational health, and mentoring teammates at all levels to do the same. - Being passionate about the work you are doing and contributing positively to Strava's inclusive and collaborative team culture and values. WHAT YOU'LL BRING TO THE TEAM: - 5+ years of experience building and operating complex, production AI or backend systems at scale, with a track record of decomposing large technical problems into well-scoped execution across teams. - Demonstrated experience building AI platform tooling or developer-facing infrastructure ideally for LLM or ML systems with a strong instinct for API design, versioning, and self-serve patterns. - Hands-on experience building with large language models in production: agentic workflows, prompt and context engineering, RAG architectures, embedding pipelines, fine-tuning workflows, or LLM evaluation frameworks and tools like Langchain . - Proficiency in search systems (Elasticsearch/OpenSearch, Vector Search, etc) - Proficiency in backend service development on cloud environments (AWS preferred), using Python, Go. Solid understanding of distributed systems and containerized infrastructure (Kubernetes, Docker). - Strong technical leadership: ability to lead multi-team projects, define technical direction, and grow engineers at multiple levels. - Deep curiosity about the evolving GenAI landscape: model capabilities, agent frameworks, multimodal systems: and strong judgment on where and how to apply them to real product problems. - Strong communication and collaboration skills, with the ability to align cross-functional partners around technical direction and build organizational trust in the platforms your team ships. For information on benefits, please click here https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub. WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: San Francisco Workplace: Hybrid Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit. ABOUT THE COMPANY Our client is an early-stage, San Francisco-based AI startup building the operating system for family law. Their platform automates the most time-intensive parts of legal practice — client intake, financial disclosures, document preparation, case management, and client collaboration — helping family law firms modernize and scale without adding headcount. Founded in 2025, the company is already working with real customers and actively closing a seed round, with $XM signed to date.   THE MISSION To reduce the emotional and financial burden of divorce for millions of families — and empower the legal professionals who serve them — by transforming a fragmented, manual process into a guided, intelligent, AI-driven experience.   THE OPPORTUNITY This is a co-founder seat, not a hire. You're joining at the inflection point: real product, real customers, seed round closing. As the first technical leader, you'll own the full stack — architecture, AI infrastructure, engineering culture, and execution velocity. You'll work shoulder-to-shoulder with the founding team to define how AI reshapes one of the largest, most underserved verticals in legal services. If you've been waiting for a founding opportunity where the market is real, the mission matters, and the equity is worth the bet — this is it.   WHAT YOU'LL DO - Own and define end-to-end technical architecture of the platform - Write and ship production code daily alongside the founding team - Architect and scale AI agent infrastructure for legal workflows — billing, financial layers, document automation, collections, and client collaboration - Build and scale the engineering team from scratch — hiring, mentoring, and establishing culture - Partner with founders on product roadmap, fundraising narrative, and company strategy - Ensure security, compliance, and scalability of a document-heavy, regulated-industry platform - Drive rapid iteration cycles and maintain startup velocity through seed close and beyond   WHAT YOU BRING Must-Haves: - 8+ years of software engineering experience, with 3–5+ years in technical leadership - Deeply hands-on — you still write and ship production code regularly - Proven experience building AI-native, workflow-heavy, or document-centric SaaS products - Proficiency with modern AI/ML stacks: LLMs, RAG, and agentic frameworks (LangChain/LangGraph, OpenAI/Claude APIs) - Strong backend and cloud infrastructure expertise (GCP/AWS, Python, Node.js, Kubernetes) - Experience building engineering teams in a 0→1 environment - Based in the SF Bay Area or willing to relocate - Financially comfortable with a founder salary model during the build phase — equity is the upside Nice-to-Haves: - Exposure to legal tech, compliance-heavy, or regulated-industry products - Experience with document automation platforms - Prior founding experience or early employee (1–50 person company) - Background at Big Tech or high-growth SaaS - Genuine interest in access to justice and modernizing legal services   KEY SUCCESS DRIVERS - Builder-first — you ship fast, don't wait for perfect conditions, and take pride in what you launch - Full ownership — you treat the product and team like they're yours, because they will be - Systems thinker — you design for agentic workflows and automation, not just feature lists - Ambiguity-tolerant — you thrive in 0→1 environments without a defined playbook - Mission-aligned — you're genuinely excited about AI's role in transforming legal services - Speed over perfection — you iterate fast, learn faster, and course-correct in real time   WHY JOIN? Compensation & Equity: - 7-10% founder-level equity — significantly above market, reflecting a true founding relationship - Base salary: ~$4,000/month during the pre-seed phase, with a clear normalization trigger post-seed close - Upside is entirely equity-driven, structured for long-term wealth creation What Makes This Rare: - Co-founder title and seat — not a VP/Director scope with imposed constraints - Real product traction and paying customers before you join - Seed round in progress: $XM already signed - Recognized by TechCrunch Disrupt Startup Battlefield and Stanford CodeX FutureLaw - Greenfield opportunity to define the technical foundation of a category-creating company INTERVIEWING PROCESS - Intro Call - Level 1 — Technical Deep-Dive - Level 2 — Take-Home or Live Build Exercise - Level 3 — In-Person Co-Founder Day (half day, SF) - Reference Checks + Offer We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.

Location: Distributed About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations Cincinatti, OH What you will do as a Customer Engineer The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire customer journey. Key Responsibilities Technical Validation: Partner closely with Account Executives to lead technical deep-dive discovery, capture business requirements, and map complex customer infrastructure - DNS, CDN, Zero Trust, Network Security, Workers - to fit-for-purpose Cloudflare architectures and bespoke solutions. Define, scope, success criteria, and technical evaluations plans for Proof of Concepts (PoCs) and Technical Validations. Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, and reliability challenges. Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle. Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional services) being an integral part of all proposals. Customer Adoption & Value Realization: Provide oversight to technical onboarding and implementation, but not execute the implementation, serving as the primary executive and engineering contact for the customer. Design structured migration and onboarding blueprints tailored to the customer’s environment (e.g. DNS migrations, Zero Trust rollouts, WAF tuning guidance), and act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices.  Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk. Commercial Accountability & Expansion: Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives. Trusted Advisory: Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. Provide thought partnership on architecture, AI control layers, security posture, and deployment confidence. Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes. AI Orchestration & Workflow Automation: Leverage AI agents, Large Language Models (LLMs), and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, basic telemetry monitoring, and internal/external documentation, reclaiming your time for strategic customer advisory. Education & Enablement: Partner closely with the Enablement Team to design, build, and govern technical resources. Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization. Minimum Qualifications Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services,  Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Architectural Mindset: Ability to white-board, design, and articulate complex enterprise network and security architectures clearly. Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives. Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise sales cycles. Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy. Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least four of the technical areas below: Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS. Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts. Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3. AI Proficiency: Familiarity with prompt engineering, AI-assisted scripting and log analysis, LLM utilization, and workflow automation to augment everyday CE workflows. Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments. Strongly Preferred Qualifications (The "Good-to-Haves") Technical Enablement: Track record of creating and delivering technical enablement - workshops, code samples, documentation, or developer onboarding - that accelerates customer adoption of complex platforms. Applied AI Knowledge: Experience with LLM orchestration, Retrieval-Augmented Generation (RAG) architectures, and model-access controls. Regulatory Knowledge: Understanding of regulatory requirements such as PCI DSS, HIPAA, and SOC 2. Hyperscaler / Digital Native Background: Talent coming out of hyperscalers, digital natives, distributed systems environments, or startups is strongly valued for its deeper cloud fluency and advanced architecture depth. Education Undergraduate or graduate degree in Computer Science, Engineering, or a related field. Travel This role may require travel up to 20–50% to attend customer meetings, conferences, industry events, and in-person team collaboration. Compensation This role features a competitive base salary and a variable compensation structure tied directly to the successful execution of full-lifecycle commercial targets, including new business acquisition, ongoing adoption milestones, and overall account expansion. Compensation may be adjusted depending on work location. This role is eligible to participate in Cloudflare’s equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Location: Warsaw, Poland Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! Tickmill is looking to hire a Senior AI/ML Engineer (AI Lead) to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. About Tickmill. Tickmill is an award-winning, multi-regulated broker offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options). Founded in 2014, the Tickmill Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields. Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth. Join the Tigers! What does the role look like? The Senior AI/ML Engineer (AI Lead) will have the chance to: • Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments. • Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact. • Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management. • Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies. • Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts. • Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact. • Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations. • Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness. • Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery. • Mentor team members and promote best practices in production AI, MLOps, and applied machine learning delivery. What do you need to succeed in this role? • 5–8+ years of experience building and deploying machine learning models in production environments (not just experimentation). • Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability). • Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability). • Hands-on experience with large-scale data processing (Spark / PySpark). • Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility. • Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows. • Strong SQL skills and experience working with large, complex datasets in real-world environments. • Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements. • Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems. • Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly. • Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness. The below are considered as a plus: • Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions. • Experience with real-time or streaming ML systems. • Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data. • Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards). • Experience contributing to team standards, mentoring, or leading applied AI delivery. By joining us, you can expect: • Unique opportunity for a career in a global, fast-growing company. • Attractive remuneration package based on qualifications and experience. • Opportunities to learn and grow through our “Employee Training & Development program”. • Hybrid work flexibility. • Multiple events to bond with the team and the group. • Birthday and loyalty benefits. Make your next career step and apply NOW! *Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.

О ПРОЕКТЕ Команда занимается развитием внутренней AI/ML-платформы, AutoML, разработкой LLM/NLP-решений, мониторингом качества моделей на крупном финтех-проекте. ПРЕДСТОЯЩИЕ ЗАДАЧИ • Разработка и развитие ML/LLM-сценариев для production; • Работа с AutoML, NLP и RAG-пайплайнами; • Оптимизация качества и стабильности ML-решений; • Интеграция с MLOps/DE-инфраструктурой; • Быстрое прототипирование и проектирование AI-решений. ОЖИДАНИЯ ОТ КАНДИДАТА • 3+ лет опыта в DS/ML; • Хороший Python и уверенный ML-стек (Sklearn, CatBoost/LightGBM/XGBoost, Pandas, NumPy), опыт с табличными данными; • Опыт с LLM/NLP (для проекта в данном направлении); • Опыт работы с Spark/Hadoop/Hive; • Понимание production ML-процессов. БУДЕТ ПЛЮСОМ • PyTorch / DL; • Open-source contribution; • Full-stack опыт. УСЛОВИЯ РАБОТЫ • Оформление по ТК или ИП в аккредитованную ИТ-компанию; • Сильная инженерная команда и обмен экспертизой; • Гибридный или удаленный формат работы (РФ!); • ДМС со стоматологией с 1-го дня; • Предоставление техники (на выбор, по запросу).

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity The Compliance team's primary objective is to ensure that OKX operates in accordance with regulatory requirements while maintaining the highest ethical and moral standards. The team owns the full compliance engineering stack: KYC onboarding and refresh, sanctions / PEP / adverse-media screening, transaction monitoring (TM) and travel-rule enforcement, case management, and regulatory reporting. We achieve this by developing compliance service solutions, integrating with KYC & AML vendors, and enabling robust business growth, which ultimately strengthens user trust in our platform. Our ultimate goal is to create a culture of compliance excellence, where innovation and responsible business practices are seamlessly integrated. In compliance, a system that is mostly right is wrong — so every control we build must be deterministic in its enforcement, complete in its coverage, and explainable in its outcome. What You’ll Be Doing Formulate, select, and develop technical schemes for platform projects across the compliance domain — KYC onboarding flows, identity verification and refresh, sanctions / PEP / adverse-media screening, transaction monitoring, travel-rule, case management, and regulatory reporting — including AI/ML-powered features such as intelligent screening disambiguation, document verification, anomaly detection, automated risk scoring, and analyst-assist agents. Organize and coordinate resources, leading project research and development, troubleshoot problems, and ensure quality and timely completion — including delivery of AI model integration work within KYC, screening, and monitoring workflows. Facilitate cross-team communication and promote teamwork efficiency through code quality control and collaboration, including partnering with Data Science, Risk, and Legal to productionize models and ensure reliable, auditable inference infrastructure. Define where probabilistic AI is appropriate versus where deterministic logic is mandatory — and design the boundary cleanly so models assist without compromising auditability or enforcement integrity. Undertake team tasks and cultivate technical talents in the industry, with a focus on building AI engineering best practices across the compliance engineering team — patterns for agentic coding, prompt libraries, eval suites, and human-in-the-loop review of AI-generated work in a regulated environment. What We Look For In You A compliance-first systems mindset — you instinctively reach for state machines, idempotency keys, exactly-once semantics, reconciliation jobs and immutable audit logs. You understand that in compliance, false negatives cost millions and false positives cost trust, and you design accordingly. Prior experience in KYC, AML, sanctions, fraud, or payments is a strong plus; experience surviving a regulatory audit is an even stronger plus. Daily, fluent use of modern AI coding tools — Claude Code, Cursor, GitHub Copilot, Codex CLI, or equivalents. You can describe the specific workflows you run, the failure modes you have hit, and the guardrails you have built around AI-generated code. AI fluency is required, not nice-to-have. Production experience integrating AI/ML model inference into Java services — REST/gRPC-based model serving, feature engineering pipelines, latency-sensitive inference optimization, graceful degradation, and drift / rollback playbooks. Hands-on experience with LLM application patterns — at least one of: RAG pipelines (vector store + retrieval + grounding) for policy / KYC / case lookup, agentic workflows (tool use, multi-step reasoning, validation loops) for analyst assistance, or LLM-based classification / extraction shipped to production. Discipline around AI output — you do not ship LLM features without evals, hallucination tests, prompt regression suites, and human-in-the-loop review for high-stakes decisions. You have an opinion on when to reach for a frontier model vs. a fine-tuned small model vs. a deterministic rule, and can defend that trade-off to a regulator. Exposure to LLM integration or AI agent frameworks is a strong plus — e.g. prompt engineering at the system level, RAG pipelines, or orchestrating AI workflows within a regulated environment. Good understanding of software engineering basics, distributed system principles, including CAP, consistency, idempotency, and exactly-once vs at-least-once semantics. Clear logic, quick thinking, and good communication skills — including the ability to write clearly for non-engineers (compliance officers, auditors, regulators). AI Proficiency Expectations & Interview Process AI fluency is a required engineering competency for this role, on the same level as ‘can write good Java’. We will assess it explicitly during the interview, and a strong showing here is a meaningful plus: AI-augmented workflow demo — walk us through how you use AI tools day-to-day. The prompts, the tasks you delegate to an agent vs. write yourself, how you review AI-generated diffs, and how you measure the impact (commit velocity, defect rate, test coverage). Concrete examples beat slogans. Live agentic exercise — a working session using the AI coding agent of your choice on a realistic compliance-flavoured problem. We look at how you scope, prompt, validate, and integrate AI output, not whether the agent gets it right first try. Design discussion with a probabilistic twist — expect at least one system-design question where the right answer involves deciding when not to use an LLM, and how to design the deterministic fallback. We hire engineers who can defend that boundary. Evaluation & guardrails — be ready to discuss an eval suite or guardrail you have built for an AI feature in production (e.g. an LLM-assisted SAR narrative drafting tool, an AI-assisted KYC document review step, or screening-hit disambiguation). If you have not shipped one, tell us how you would design it. Perks & Benefits Competitive total compensation package L&D programs and education subsidy for employees' growth and development — including budget for AI tools, courses, and conferences Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: United Kingdom; Canada; United States About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a skilled AI Engineer with at least 2 years of hands-on experience in developing, deploying, and optimizing AI and machine learning solutions. You will work closely with product, engineering, and data teams to design intelligent systems, integrate AI models into production environments, and contribute to cutting-edge AI initiatives. This is an exciting opportunity for someone passionate about machine learning, generative AI, LLMs, automation, and scalable AI infrastructure in a fully remote environment. Key Responsibilities Design, build, and deploy AI/ML models for real-world applications. Develop and optimize AI-powered features using modern frameworks and APIs. Work with Large Language Models (LLMs) such as GPT, Claude, or open-source alternatives. Build AI pipelines for data processing, training, inference, and monitoring. Collaborate with cross-functional teams to translate business needs into AI solutions. Integrate AI services into web applications, SaaS platforms, and internal tools. Fine-tune and evaluate machine learning models for performance and scalability. Maintain documentation and ensure AI systems follow security and compliance best practices. Stay updated with the latest advancements in AI, machine learning, and automation technologies. Requirements 2+ years of experience as an AI Engineer, Machine Learning Engineer, or similar role. Strong experience with Python and AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, or LangChain. Experience working with LLMs, generative AI, prompt engineering, or AI agents . Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG). Experience deploying models using cloud platforms like AWS, Azure, or Google Cloud. Understanding of APIs, microservices, and backend development. Experience with Docker, Git, and CI/CD workflows. Strong analytical and problem-solving skills. Excellent communication skills and ability to work remotely with global teams. Bachelor’s degree in Computer Science, AI, Data Science, or related field preferred. Experience with AI automation tools and agent frameworks. Knowledge of MLOps and model monitoring tools. Familiarity with NLP, computer vision, or recommendation systems. Experience building AI SaaS products or chatbots. Exposure to FastAPI, Node.js, or React-based applications. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Задачи: — Продуктизация ML-моделей и пайплайнов — Интеграция моделей в backend и бизнес-контуры — Разработка API и сервисов для ML — Работа со стримингом данных (Kafka) — Участие в RnD и пилотировании новых ML-решений Требования: — Опыт разработки на Python от 3–4 лет — Высшее образование (законченное) — Опыт работы с ML-проектами (CV, NLP, RAG) — Опыт разработки REST API (FastAPI / Flask) — Опыт работы с Kafka — Понимание микросервисной архитектуры и сетевого взаимодействия — Базовое понимание Kubernetes — Опыт работы с SQL на среднем уровне — Умение работать с кодом Data Science и адаптировать его под production Будет плюсом: — Опыт работы с Airflow — Опыт работы с Hadoop / Spark Условия: — ДМС со стоматологией — Компенсация фитнеса — Скидки на курсы английского (Skyeng) и в кино — Индексация зарплаты — Современная техника для работы — IT-аккредитация

Location: Latin America Company Intro At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages . We are a well-funded startup with an enviable portfolio of clients including Anthropic , Amazon , Microsoft , Poolside , Recraft ,  and Shopify . Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin , CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA , UK , the Netherlands , Israel , Czech Republic , Serbia , and more. About the Role Technical consultants play a key role in our company, ensuring top-level delivery of our product, its correct configuration, and the deployment of tailored AI data solutions that meet our customers’ needs and deliver an exceptional experience working with us. As part of this role, you will not only design and implement data labeling pipelines but also act as a trusted technical advisor for our customers - helping them understand their data needs, discover new opportunities, and build scalable AI solutions. We are looking for a person with more than 3 years of solid technical background, who feels comfortable working in technical environments, solving data-related tasks using Python and AI, and communicating directly with customers. You should be a confident communicator able to engage with both technical and executive stakeholders and collaborate closely with our commercial team. Responsibilities 1. Client Ownership & Communication Act as the primary technical point of contact for customers across technical and executive stakeholders. Lead discovery conversations to deeply understand client goals, problems and quality criteria. Translate client needs into clear, actionable solution designs and delivery plans. Advise customers on best practices in data collection, data quality, evaluation, and model training workflows. Set expectations proactively, communicate progress regularly, and manage risks and trade-offs transparently. Identify expansion opportunities and additional ways Toloka can create value through data and AI solutions. 2. Solution Design & Delivery Design end-to-end data solutions using Toloka’s platform, selecting appropriate components, workflows, and quality controls. Configure data labeling components and quality controls, develop user interfaces and AI-driven tooling (e.g. agentic systems, RAGs, synthetic data generation), and integrate them into end-to-end automated pipelines for AI training and evaluation. Run experiments and pilots to validate quality, throughput, and cost assumptions. Lead technical execution during delivery, coordinating internal teams and external stakeholders as needed. Ensure solutions meet agreed quality, performance, and scalability requirements. 3. End-to-End Ownership & Project Management Own delivery outcomes holistically - including technical performance, quality, timelines, and financial efficiency. Monitor key KPIs (e.g. throughput, quality metrics, Gross Margin, Contribution Margin) and act on deviations. Prioritize work based on customer impact and business value. Analyze data to identify failure modes, inefficiencies, and opportunities for improvement. Continuously optimize solutions through iteration, automation, and adoption of new technologies. Troubleshoot delivery, process, or technical issues in collaboration with support, infrastructure, and product teams. Drive solutions toward stable operation with minimal ongoing maintenance. Requirements Core Experience Experience as a Solution Engineer, Technical Solutions Engineer, Data Scientist, Data/Systems Analyst, or Technical Project Manager. Proven experience owning projects end-to-end, including scoping, delivery, and stakeholder management. Direct experience working with external customers on technical projects (requirements gathering, delivery, iteration). Technical Skills Strong Python skills for data manipulation (e.g. NumPy, pandas), natural language processing (e.g. NLTK, spaCy), and building lightweight web services or tools (e.g. FastAPI, Flask). Solid understanding of ML concepts and data workflows; familiarity with LLMs and prompt engineering is a strong plus. Experience designing multi-stage pipelines and complex systems. Understanding of software development fundamentals: version control, testing, MVPs, iterative development etc.. Bachelor’s or Master’s degree in Data Science, ML/AI, Software Engineering, or a related quantitative field such as Physics or Applied Mathematics, with strong analytical foundations. Ability to reason about trade-offs between quality, speed, cost, and scalability. Communication & Ownership Excellent English communication skills (B2+), with the ability to explain complex technical concepts to non-technical audiences. Confidence working with data engineers, ML engineers, and researchers from leading tech companies. Strong ownership mindset: comfortable being accountable for outcomes, not just tasks. Ability to manage multiple projects in fast-paced, ambiguous environments. Nice to have Experience with crowdsourcing, expert workflows, or large-scale data labeling. Experience working on ML training, evaluation, or agentic systems. Familiarity with quality frameworks, audits, or data validation pipelines. [Important Notice] Scam Alert Regarding Fake Job Postings It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants.Please be aware: Official Communication: Our recruiting team will only contact you from an official " toloka.ai " email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc,  or other personal or seemingly business email accounts. Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process. Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it. Thank you for your vigilance!

Основные направления: — Продуктизация ML-моделей и пайплайнов — Интеграция моделей в backend и бизнес-контуры — Разработка API и сервисов для ML — Работа со стримингом данных (Kafka) — Участие в RnD и пилотировании новых ML-решений Обязанности: — Продуктизация и внедрение ML-моделей в production — Рефакторинг кода от DS-команд под production-стандарты — Разработка backend-сервисов и REST API для ML-решений — Интеграция сервисов через Kafka и микросервисную архитектуру — Участие в построении и развитии ML-пайплайнов — Взаимодействие с DS, MLOps и аналитиками — Участие в архитектурных решениях и RnD-задачах Требования: — Опыт разработки на Python от 3–4 лет — Обязательно высшее образование (законченное) — Опыт работы с ML-проектами (CV, NLP, RAG) — Опыт разработки REST API (FastAPI / Flask) — Опыт работы с Kafka — Понимание микросервисной архитектуры и сетевого взаимодействия — Базовое понимание Kubernetes — Опыт работы с SQL на среднем уровне — Умение работать с кодом Data Science и адаптировать его под production Будет плюсом: — Опыт работы с Airflow — Опыт работы с Hadoop / Spark Условия: -ДМС со стоматологией -Компенсация фитнеса -Скидки на курсы английского (Skyeng) и в кино -Индексация зарплаты -Современная техника для работы -IT-аккредитация

Location: Europe; Brussels; Munich; London; Edinburgh; Paris; Berlin; United Kingdom; France; Frankfurt; Germany Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ABOUT NORTH: North https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. WHY THIS ROLE? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one. In this role, you will: - Work closely with our enterprise customers to translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources, with enterprise-grade reliability and performance - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualisation through production - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution - Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization - Travel up to 20–40% to work on-site with customers and partners You may be a good fit if: - You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code - You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute - You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks - You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency - You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs - You have experience owning the full scope of a use case end-to-end - You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting It's a bonus if you have: - Experience setting architectural standards for AI and agentic systems across distributed teams - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms) - Experience with enterprise security, compliance, or auditability requirements for AI systems FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Hong Kong, Hong Kong SAR Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity You will be responsible for product planning and solution design for an enterprise-grade AI Native engineering platform, driving the deep integration of AI Agents, AI Coding, knowledge capabilities, and engineering platform systems. The goal is to build an intelligent product system covering requirement analysis, solution design, development collaboration, testing validation, environment orchestration, and knowledge accumulation.This role serves complex engineering processes and multi-role collaboration scenarios. You are expected to design AI product capabilities that can be embedded into workflows, measured for impact, and continuously evolved in real enterprise environments, enabling the product to scale from pilot adoption to broad organizational rollout. What You’ll Be Doing Lead the product planning, requirement analysis, and solution design of the AI Native engineering platform, and drive continuous product evolution and adoption. Develop a deep understanding of the end-to-end engineering lifecycle, and translate the core scenarios and collaboration patterns of product, design, engineering, QA, and operations teams into structured product solutions. Design AI Agent capabilities for engineering scenarios , including requirement analysis, solution generation, coding collaboration, test generation, environment orchestration, and knowledge accumulation. Drive the integration of AI capabilities with code repositories, CI/CD pipelines, testing platforms, deployment environments, and knowledge platforms to deliver a unified end-to-end product experience. Establish mechanisms for product effectiveness evaluation, user feedback, and continuous optimization , and support the product’s scale-up from pilot validation to broad adoption. What We Look For In You Bachelor’s degree or above , preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields. 8+ years of experience in ToB products, platform products, or intelligent product solutions. Must have an engineering background , such as software development, test development, architecture, or technical product roles, with the ability to work effectively with engineering teams. Strong understanding of DevOps , engineering productivity, software delivery processes, and quality systems , with the ability to abstract and productize complex workflows. Solid understanding of AI Agent product design , with the ability to design for task execution, workflow orchestration, result validation, and delivery closure. Familiarity with mainstream AI coding products, with strong hands-on experience or product understanding of Claude Code , Codex, Cursor , and Copilot , as well as context engineering, knowledge input, tool integration, human-in-the-loop collaboration, and governance considerations. Strong structured thinking, cross-functional collaboration, and execution skills; experience with engineering platforms, DevOps platforms, platform products, or intelligent products is a plus. Nice to Haves Experience with products related to AI Agents, RAG, knowledge graphs, Copilot, or intelligent workflows . Experience building engineering platforms, DevOps platforms, or platform products from 0 to 1 or from 1 to N. Hybrid background of engineering-to-product transition , or contributions to open source, communities, or public thought leadership in AI or engineering productivity. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependents. More that we love to tell you along the process! Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: North Macedonia; Georgia; Serbia; Croatia; Slovenia; Bosnia and Herzegovina About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary As an AI Engineer, you will be responsible for developing and optimizing AI systems, integrating machine learning models into production environments, and building scalable AI-driven applications. You will contribute to everything from model experimentation to deployment and performance optimization. Key Responsibilities Design, build, and deploy AI and machine learning solutions for real-world business applications. Develop and maintain applications using Large Language Models (LLMs) such as GPT-based systems. Build AI-powered automations, copilots, chatbots, and workflow systems. Fine-tune, evaluate, and optimize machine learning models for performance and scalability. Integrate AI systems with APIs, databases, CRMs, and third-party platforms. Collaborate with product and engineering teams to translate business requirements into AI-driven solutions. Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems. Monitor model performance, reliability, and cost efficiency in production environments. Maintain documentation, testing procedures, and deployment workflows. Stay updated on the latest AI trends, frameworks, and emerging technologies. Requirements 3+ years of experience in AI Engineering, Machine Learning, or Software Engineering. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face. Experience working with LLMs, OpenAI APIs, Anthropic, Gemini, or similar AI platforms. Familiarity with vector databases, embeddings, and RAG architectures. Experience deploying AI applications using cloud platforms such as AWS, GCP, or Azure. Strong understanding of APIs, backend systems, and scalable application architecture. Experience with Docker, Git, CI/CD pipelines, and modern development practices. Excellent problem-solving and analytical thinking skills. Strong communication skills with the ability to work in remote, cross-functional teams. Bonus: Experience building AI agents, automation systems, or voice AI applications. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: South Africa; Pakistan; Philippines; United States; United Kingdom; Canada About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a highly skilled AI Engineer to design, build, and deploy AI-driven applications and machine learning solutions. You’ll work closely with product, engineering, and data teams to create intelligent systems that improve automation, customer engagement, and operational efficiency. This role is ideal for someone passionate about artificial intelligence, large language models (LLMs), machine learning infrastructure, and production-grade AI systems. Key Responsibilities Design, develop, and deploy AI and machine learning models for real-world applications. Build and optimize AI-powered tools using technologies such as OpenAI, Claude, Gemini, or open-source LLMs. Develop scalable APIs and backend services for AI applications. Fine-tune machine learning models and improve model performance. Work with structured and unstructured datasets for training and inference. Implement prompt engineering strategies and retrieval-augmented generation (RAG) pipelines. Integrate AI solutions into web platforms, CRMs, and business systems. Monitor AI model performance, reliability, and scalability in production. Collaborate with cross-functional teams to define AI product requirements and technical roadmaps. Stay updated on emerging AI technologies, frameworks, and best practices. Requirements 3+ years of experience in AI engineering, machine learning, or software engineering. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or Hugging Face. Experience working with LLMs, generative AI tools, and prompt engineering. Familiarity with vector databases, embeddings, and RAG architectures. Knowledge of cloud platforms such as AWS, GCP, or Azure. Experience building REST APIs and scalable backend systems. Understanding of MLOps, model deployment, and monitoring workflows. Strong problem-solving and analytical thinking skills. Excellent communication and collaboration abilities. Experience working in remote or distributed teams is a plus. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: Mexico; Colombia; Brazil; Chile; Argentina; Costa Rica About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Role Type: Full-time Engagement: Independent Contractor Job Summary We are looking for a highly skilled AI Engineer to design, develop, and deploy scalable AI and machine learning solutions. You’ll work closely with product, engineering, and leadership teams to build intelligent systems that power automation, analytics, conversational AI, and predictive capabilities. This role is ideal for someone passionate about artificial intelligence, large language models (LLMs), machine learning infrastructure, and solving real-world business challenges with cutting-edge technology. Key Responsibilities Design, develop, and deploy AI/ML models for production environments. Build and optimize AI-powered applications using large language models (LLMs) and generative AI tools. Develop intelligent automation workflows, chatbots, recommendation systems, and predictive analytics solutions. Fine-tune, evaluate, and improve machine learning models for performance and scalability. Collaborate with software engineers and product teams to integrate AI features into existing platforms. Work with structured and unstructured datasets for training and inference pipelines. Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems. Monitor AI systems, troubleshoot issues, and continuously improve model accuracy and efficiency. Stay updated with the latest advancements in AI, machine learning, and automation technologies. Maintain documentation for AI models, systems, and workflows. Requirements 3+ years of experience in AI engineering, machine learning, or related software engineering roles. Strong experience with Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or LangChain. Hands-on experience working with OpenAI APIs, LLMs, generative AI, or NLP systems. Experience deploying machine learning models into production environments. Familiarity with vector databases, embeddings, and RAG architectures. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Knowledge of Docker, Kubernetes, APIs, and CI/CD pipelines is a plus. Strong understanding of data structures, algorithms, and software engineering best practices. Excellent problem-solving and analytical skills. Strong communication skills and ability to work in a remote, collaborative environment. Benefits 💰 Competitive salary based on experience and location 🌎 Fully remote role with flexible work environment 🚀 Work on cutting-edge AI automation projects with real business impact 📈 Strong growth opportunity into senior AI / systems roles 🧠 Exposure to LLMs, prompt engineering, and scalable AI system design 🤝 Direct collaboration with a fast-moving, high-performance team

Location: Remote - Toronto, Ontario; Remote - Vancouver, British Columbia; Remote - Denver Workplace: Remote The Company At Nylas, we specialize in making it easier for developers to add email, calendar, and contact management features into their applications. We provide APIs, which streamline the integration of these functionalities, ensuring they are secure and effective. This enables better, safer, and more reliable communication within apps. Supporting over 100,000 developers and collaborating with more than 900 companies globally, Nylas plays a pivotal role in how digital communication tools are built and utilized. Our technology spans various sectors, from healthcare to education, simplifying the complex process of app development related to communications. By reducing the barriers in communication technology, we empower developers to innovate and enhance user interaction across platforms. THE TEAM We're looking for a Product Manager who is going to usher in the new era of integrating with communication data. We operate with a founder's mindset. You'll own outcomes end-to-end, from early discovery through shipping and scaling, with the autonomy to move fast and the judgment to know when to slow down. We share wins, dissect failures, and hold a high bar for what a developer platform can be. If you're the kind of person who spots an opportunity on Monday and has a working prototype by Tuesday, you'll fit right in. WHAT YOU'LL DO - Partner with leadership to define and execute on a particular area of the product portfolio that you own, keeping in line with the broader company objectives of unlocking AI utility, owning the AI agent comms harness, and making Nylas the fastest time to value for AI-based workflows. - Formulate technically complex and nuanced subject matter into clear business value. You can make sense of a deeply technical domain, reason through it, and translate it into a confident business bet. - Roll up your sleeves with Marketing to co-own GTM strategy, shaping how Nylas is positioned in a fast-moving AI landscape, crafting narratives that resonate with developers, and driving execution through launch and beyond. - Deeply understand how developers are building AI-powered applications today: what they're reaching for, where they're getting stuck, and where Nylas can become an indispensable part of that stack. - Lead discovery with our developer community and enterprise partners through closed betas, feedback loops, and continuous validation, building what the market needs before they can articulate it. - Own the documentation and launch lifecycle, ensuring every release sets a new standard for developer experience. - Move fast on low-risk problems. Don't wait when you can act. THE IDEAL CANDIDATE: - Problem-led thinking is non-negotiable. You identify and articulate user problems clearly before reaching for solutions. Your work history reflects outcomes, not just output. You can point to metrics that moved, not just features that shipped. - You are genuinely plugged into how AI is changing software development. Not because your last job required it, because you're drawn to it. You're experimenting with tools like Claude Code, Codex, or similar in your own time. You have a nuanced understanding of the AI landscape, concepts such as LLMs, agents, RAG, and embeddings, and can speak to these with depth, not just vocabulary. If you've operationalized AI-based features or built pipelines in a professional context, even better. - You have a builder's instincts. You don't wait for a designer to be free before moving on a prototype. You don't wait for an engineer to run an audit, you can orchestrate yourself. You know the difference between what requires a specialist and what you can unblock with the right tools and good judgment. You operate within safe boundaries, but you push those boundaries as far as they reasonably go. - You have strong developer empathy. You understand how developers evaluate tools, make build-vs-buy decisions, and think about integrating third-party infrastructure into their products. You don't need to have come from a connectivity or API company, but you need to understand the developer mindset deeply, especially as it's evolving in the AI era. What You Must Bring - 3+ years of product management experience working on technical products - Background in software engineering, technical product development, or demonstrated builder experience inside or outside of work - Experience collaborating closely with engineering teams on requirements, trade-offs, and technical risks - Strong communication skills across technical and non-technical stakeholders - Comfort operating with ambiguity and incomplete information Bonus Points - Experience shipping AI-powered features, workflows, or developer tools - Experience taking products from 0 → 1 in either a professional or personal capacity - Experience working with APIs, developer platforms, or infrastructure products Interview Process - Round 1 - The Intro: 30 minute discussion with the Hiring Manager - Round 2 - The Deep Dive: Take home assignment to be followed by a 60 minute presentation with a panel - Round 3- The Loop: A series of 45-minute chats with the team (max 3 hours) where we look for the "what, why, and how" behind your best work. During the various discussions, candidates selected to meet with us are strongly encouraged to not only discuss their knowledge, skills, experience, and abilities but also to showcase examples of their current or previous work. We expect you to clearly outline the "what," "why," and "how" behind your contributions. The estimated base salary range for this position is $120,000 - 160,000 CAD. Actual compensation will be determined based on individual qualifications, which are objectively assessed during the interview process. Factors influencing salary include knowledge, skills, experience, and abilities. Nylas is registered as an employer in many, but not all, states/provinces. If you are not located in or able to work from a state/province where Nylas is registered, you will not be eligible for employment. Visa sponsorship may not be available in certain remote locations.

Location: Remote (Costa Rica) At Livefront, we help companies design and build world-class digital products that command attention and inspire joy. We’ve helped household names like CVS, Samsung, General Mills, and Optum create experiences that have reached millions of people, and startups like HomeSpotter and Credly build entirely new businesses that challenge their industries’ status quo. We’re looking for an AI Solutions Engineer to join our team. This is a senior-level position with the opportunity to work remotely in Costa Rica. Who you are You're a thoughtful, creative problem-solving engineer who thrives at the intersection of cutting-edge technology and real-world impact. With deep experience in AI, LLMs, RAG-based architectures, and machine learning, you have an impeccable intuition for turning emerging capabilities into innovative, practical solutions. You’re equally adept at rapidly prototyping ideas in scrappy R&D sprints as you are at shipping robust, scalable code into production. Navigating both architectural design and hands-on implementation comes naturally to you, and you quickly master unfamiliar technologies. You articulate complex technical requirements clearly to internal teams and confidently engage in strategic discussions with client partners. Your engineering principles are mature yet adaptable, shaped by continuous learning, collaboration, and the evolving technological landscape. You're curious and pragmatic, driven by craft to build intelligent systems that are intuitive, performant, and thoughtfully designed. You're passionate about shaping an ethical, innovative, and impactful future for AI. What you will be doing Work closely with clients to understand their business goals around implementing AI technologies, present sustainable and achievable technical solutions, and adjust strategies based on feedback. Guide and mentor engineering teams with your AI expertise, both internally to Livefront and externally with the client, by setting technical standards, conducting code reviews, and contributing to product vision. Engage in technical spikes to explore new technologies and methods. Lead the design of robust architectures tailored to client needs and implement these solutions hands-on, ensuring scalability and maintainability. Design, develop, and integrate APIs, data pipelines, and end-to-end infrastructure that ensure seamless communication between systems. Help optimize performance and enable AI models to be useful, scalable, and maintainable. Adapt your skills across diverse projects, including API design, real-time technical support, and DevOps, demonstrating versatility and responsiveness to varied client needs. Collaborate cross-functionally, streamlining communication between backend teams, frontend teams, designers, and other team members. Why you should apply You want to work with passionate and talented people who are always looking for ways to make things better. You desire a work environment where respect, mutual trust, and egoless collaboration are paramount. You want colleagues who take their work seriously but not themselves, and who know how to find fun in the work. You like being part of a team that has a reputation for excellence and gives back to the community by educating, mentoring, and sponsoring. You want to work on products and accounts that have outsized impact and reach. You believe in sweating the details, committing to quality, and taking pride in going the extra mile. What you bring to the table At least 7-10 years of software engineering experience, preferably in a consulting environment or as part of an in-house, cross-functional product team. Full-stack engineering experience in web or native mobile. Experience with Python/JavaScript, Cloud Infrastructure & DevOps, LLMs & RAG Architecture, and event-driven architectures. Data engineering experience that will enable successful AI implementations. Demonstrated expertise in architecting, building, maintaining, and scaling modern software on various platforms. Experience designing APIs and writing API specifications. Ability to clearly articulate technical requirements to other engineers. A keen sense of security: you're able to think around corners and see potential risks. A talent for communicating directly with clients, managing expectations, and explaining advanced technical concepts and their implications. Excellent communication skills and a strong ability to present and defend technical and architectural choices persuasively. Advanced English proficiency. Exceptional problem-solving skills. Above-average discipline and personal organization skills. A demonstrated hunger for personal and professional growth. A self-evident love and care for the craft of software engineering. Comfort with occasional travel to our HQ in MN. Bonus points if you... Have strong illustration chops as it relates to technical diagramming. Speak, write, and/or educate publicly about technical topics. Have publicly released your own personal, self-started products or apps. Enjoy tinkering with languages and frameworks such as Tensorflow, SciKit Learn, or training machine learning models from scratch. Have experience with advanced prompt engineering techniques. Enjoy tinkering with emerging languages and platforms such as Go, Rust, Alexa, and/or Unity. What to expect When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn, etc). Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete. Additional information We go out of our way to evaluate all employees and job applicants equally based on merit, competence, and qualifications. We encourage candidates from all backgrounds to apply and consider all qualified applicants.