AI-инженер (LLM, агенты, AI product) вакансии - удалённо

✔️ 5+ лет опыта разработки на Python. ✔️ Опыт создания AI-агентов и LLM-приложений.

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

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

Runway is looking for a Prototype Researcher to design and build experimental AI experiences, prototypes, and demonstrations that communicate emerging research capabilities.

Location: Remote; Seattle, WA; London; New York, NY; San Francisco, CA Workplace: Remote We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. WHY THIS MATTERS Runway is building AI to simulate the world. We think world models, not language models alone, are the path to general-purpose simulation: systems that experience the world, learn from their mistakes, and change how stories get told, how science gets done, and how the next frontiers of humanity are reached. Applied AI is where that research meets a customer with a deadline. Every one of the world's largest studios, brands, and platforms hits a moment where Runway stops being a demo and becomes the way they actually make things. Our team exists for that moment, and we organize around one question: what's blocking this customer from production, and how do we remove it? ABOUT THE ROLE This is a role for people who want to own a problem, not an account. You'll sit with the biggest studios, brands, and Fortune 100 companies in the world, figure out what's actually standing between them and production, and build whatever removes it. Some weeks that's a workflow. Some weeks it's a plugin or an integration nobody has written yet. Some weeks it's getting a room of executives to make a decision they've been putting off. Your work will be on screen: Emmy-winning shows, Oscar-winning films, Super Bowl commercials, the stuff people actually watch. And the things you build for one customer tend to become product for all of them. Our team's first Shopify plugin started as a customer blocker and was in engineering's hands within a few weeks. We treat this team as R&D for that reason, not as a cost center. We have offices in NYC, San Francisco, Seattle, and London. NO TWO WEEKS ARE THE SAME, BUT YOU CAN EXPECT TO: - Find the real problem: sit with the creative, technical, and executive teams at a customer, map how they actually work, and locate the blocker between them and production. Usually it's one of three things: a missing integration, an unproven pipeline, or a stakeholder who isn't convinced yet. - Build the first of its kind: the demo that shows a studio head or a Fortune 100 CMO something nobody has shown them before. Working proofs of concept on the customer's own brand, footage, or catalog, often built in a day or two before the meeting, and the best of them become product for everyone. - Make it reusable: turn the one-off that unblocked one customer into the workflow, plugin, or integration the next ten customers start from. - Run the evaluation: own evaluation plans end to end, guide managed trials, build tailored demos on the customer's own footage and brand, and carry the technical side of deal cycles with AEs. - Scope deployments that land: 4–12 week engagements with customer-defined success criteria, a hands-on builder and an executive sponsor on their side from day one, and enough discipline to keep them on scope when the asks start piling up. - Get customers to production fast: take new technical and non-technical customers from signed contract to first production call in days rather than quarters, grow API-only accounts into Platform + API, and fix the onboarding so the support tickets stop coming. - Present to anyone: walk an analyst through a pipeline in the morning and a studio head through a production plan in the afternoon. - Bring the field back to the product: embed with Product, Engineering, and Creative to turn what you saw at the customer into roadmap. Every repeat ask is a product requirement, not a patch. - Measure what the customer measures: time to production, usage before and after a project, what they shipped because you were there. We track our own numbers in Salesforce and the warehouse; you'll own yours. WHAT WE VALUE - People who aren't satisfied with surface-level answers and will go into the data, the code, and the room to find the real one - Low ego: the customer's outcome matters more than who gets the credit - Comfort with open-ended problems in unstructured environments, and the instinct to create structure instead of waiting for it - Builders who would rather prototype than debate, and who keep iterating with the customer until it actually works - Adaptive and introspective: willing to learn, guide, lead, and follow WHAT WE NEED - You build things that run in production. Python or TypeScript, APIs, integrations, and data pipelines. Whether you write the code yourself or with coding agents, you can read it, debug it when it breaks, and explain line by line why it's built that way, including to a customer's engineering team. You've shipped something a customer actually ran: a workflow, an integration, a plugin, or an internal tool. - You've deployed AI or ML systems and integrations inside complex organizations and can point to the outcome, not just the delivery - You can hold a room of executives and a room of engineers, and translate between the two. Some of those rooms are at the customer, so expect some travel. - Nice to have: data tooling (SQL, BigQuery, Retool), or experience in media, entertainment, or advertising production Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Design and build production RAG systems and AI agents. Run open-source LLMs self-hosted, from model selection to serving and optimization.

Автоматизировать производство и публикацию 10 AI-Reels ежедневно. На вход — готовые тексты-сценарии.

-Разработка, тестирование и оптимизация промтов (Prompt Engineering) внутри системы речевой аналитики для точного тегирования, классификации и определения скрытых «болей» клиентов в диалогах с ботами. -Мониторинг и регулярный аудит диалогов ботов с клиентами банка для поиска системных сбоев, ложных срабатываний и «тупиков» в логике роботов.

– Разрабатывать AI-решения поверх нашей платформы: agentic workflows, tool calling, RAG, memory и human-in-the-loop контуры. – Проектировать multi-agent системы без жёсткой привязки к конкретному фреймворку или SDK — с логикой взаимодействия агентов, состоянием, памятью, маршрутизацией и обработкой ошибок.

We are looking for a Head of AI / AI Strategic Consultant who will play a key role in shaping AI strategies for enterprise clients. This position blends AI expertise, strategic advisory, and technical leadership.

— Поддержка и развитие AI-сервиса на Python и LangChain. — Интеграция LLM-моделей, разработка AI-агентов и RAG-систем.

Location: United Kingdom; Brazil; United Arab Emirates; Ireland; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Switzerland; Portugal; Lithuania; South Africa; Czech Republic; Canada; Hungary; Mexico; Chile; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   Growth at Kraken is being rebuilt around an AI-native platform. Instead of people manually building audiences, writing copy, adjusting budgets, and scheduling sends, agents find opportunities, make decisions, and execute across paid, organic, and lifecycle channels. They learn from every result and keep going. People still run the system. Operators use a central hub to set the rules the agents follow, review and approve what they produce, and handle exceptions when something doesn’t fit. The platform also has to work across many markets and languages, and it operates in a regulated industry, so there are compliance checks and approval steps built in. The team is a small, cross-functional group of growth, product, and engineering people who build this platform and run it day to day. We ship often, learn fast, and raise the quality bar with every release. You will work most closely with the engineers building the platform, the product team defining how operators use it, and the operators who rely on it every day. QA and operations is how the whole team knows the platform can be trusted.   THE OPPORTUNITY You will own day-to-day operations and QA for our internal growth platform. You test it, catch problems before our customers do, keep approvals and exception queues moving, and report on how it’s performing. You will work closely with product, engineering and operators to make sure the platform works and keeps working. - This is a hands-on, detail-focused role. You will spend your days in the product, testing what’s new, checking what should already work, and writing up what you find so it gets fixed. - Test the platform regularly. Cover new releases, rule changes, and edge cases, and run regression checks to make sure existing features still work. - Find bugs and document them clearly, with steps to reproduce, severity, and impact. Follow them through until engineering fixes them and you’ve verified the fix. - Monitor platform performance and agent activity, flag anything that looks wrong, and escalate it to the right person. - Work the approval queues daily. Keep items moving and make sure nothing is left unreviewed. - Check agent output against defined checklists and standards, and escalate anything unclear or risky.Note where flows are confusing or inconsistent, and flag them to the team. - Write and maintain documentation: test plans, QA checklists, runbooks, and release notes.   WHAT YOU BRING - Experience in QA, testing, operations, support, or analytics, ideally on a software product or complex system - Exceptional attention to detail. You notice what others miss and double-check your work. - A structured approach to testing. You can create and follow a test plan, and think about what could break. - Clear written communication. Your bug reports and documentation should be easy for anyone to follow. - Comfort with data. You can read a dashboard and tell when a number looks off. - Fast learner. You pick up new tools and systems quickly and ask thoughtful questions. - AI-native habits. You use AI tools in your own work every day, and you’re curious about where they get things wrong. - Prompt engineering curiosity, you don't need to be an engineer, but you are willing to learn how to communicate with AI systems precisely and improve their outputs - Reliability. You keep to a routine, keep your queues clear, and tell people early when something is stuck.   NICE TO HAVES - Experience testing software products or AI and LLM-based tools - Familiarity with Jira, Mixpanel, or similar tools - Exposure to marketing, CRM, or lifecycle messaging workflows - Interest in fintech or crypto Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Kled AI is looking for a Research Scientist Benchmarks and Evals to develop benchmarks, evaluate frontier models, and demonstrate the value of opt-in human data.

Location: Remote - Singapore Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About LangChain At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. About the role Location: Singapore - Work closely with companies on the frontier of LLM-applications, bringing ideas to production-ready apps - Collaborate on a wide variety of LLM-apps from concierge search, codegen, agentic co-pilots and more - Give technical demos the entire suite of LangChain's products - Lead trainings and workshops on best practices, targeted at developer audiences - Collaborate closely with the enterprise sales team to win deals - Collaborate closely with engineering, helping translate customer insights and feedback into product improvements - Lead internally- and externally-facing, special projects that dogfood our new products - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement How to be successful in this role - Engineers who love working with customers or are aspiring future founders - Deployed engineers / solution architects who have experience in the role at developer focused companies. - You have an engineering background and enjoy being a trusted partner to companies - You like to find a way to “make it work”. Bent towards action and service orientation. - You enjoy keeping up to date on the latest industry techniques - You’re comfortable presenting best practices to bigger teams - Bonus if familiar with LangChain or building with LLMs - Can thrive in a fast moving environment. Views unstructured environments as an opportunity to figure out the most impactful work and define the future success of the company. Startup experience is a bonus. - Ownership minded - Minimum experience of 3+ years in a similar technical role: software engineering, customer engineering Compensation & Benefits - We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Bitdeer Technologies Group is looking for an AI Engineering New College Graduate to develop large-scale AI cloud platforms, Kubernetes services, AI training and inference systems, agent platforms, and advanced AI infrastructure.

We are looking for a Senior Software Engineer II, Applied AI to join our Agentic Systems team, where you'll build AI agents that automate workflows for teams across Wrapbook. Design and build production-grade AI agents with LangGraph that automate multi-step workflows for internal teams across Wrapbook.

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

Задачи: — Владение полным циклом пользовательских сценариев с AI-агентом Upgrade на чат, голос и email: создание, оптимизация, обработка крайних случаев и рост показателя containment. — Создание сценариев в no-code инструменте Sierra Agent Studio, сотрудничество с продуктовыми группами для интеграции сервисных потоков. — Ответственность за разрешение проблем клиентов AI-агентом без участия человека. — Анализ и улучшение сценариев после запуска, включая чтение транскриптов и повышение качества взаимодействия. — Ведение портфеля сценариев по продуктам (Personal Loans, Card, BNPL, HELOC, Deposits) и установление стандартов разработки AI-опыта. Требования: — 3–5 лет опыта во Frontend Software Engineering или эквивалентный опыт в Solutions Engineering, Conversational AI или технических продуктовых ролях. — Знание поведения LLM-агентов: инструкции, вызовы инструментов, извлечение знаний и типичные ошибки. — Опыт построения оценок для недетерминированных систем: тестовые наборы, симуляции, LLM в роли судьи, регрессионные проверки. — Техническая грамотность для чтения API спецификаций, работы с backend-инженерами по REST и GraphQL, понимание авторизации и прав доступа. — Знание JavaScript/TypeScript для создания и поддержки кодированных сценариев и интеграции API в платформы Conversational AI. — Ориентация на продукт и клиента, умение читать транскрипты, забота о тоне общения и измерение успеха по решению проблем клиента. — Владение процессами выпуска, мониторинга, анализа логов и реагирования на инциденты. — Умение ясно писать и работать с неинженерами из операций, комплаенса и юридического отдела. Плюсы: — Опыт работы с Sierra Agent Studio или аналогичными no-code платформами (Decagon, Ada, Kore.ai, Google CCAI, Amazon Lex/Connect). — Опыт с Voice AI: распознавание речи, синтез речи, настройка задержек, обработка прерываний. — Знание систем контакт-центров, таких как Genesys, и проектирование передачи агентам. — Опыт в финтехе или регулируемых отраслях (UDAAP, FDCPA, TCPA, PCI, SOC 2). — Опыт в дизайне разговоров или UX-писательстве. Условия: — Конкурентная зарплата $140K-$180K CAD и опционный план. — Оплачиваемое медицинское, стоматологическое и офтальмологическое страхование. — Гибкий оплачиваемый отпуск. — Возможности профессионального роста и развития. — Оплачиваемый декретный отпуск. — Инициативы по здоровью и благополучию.