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

Развивать конвейер обработки товаров: получать данные и фотографии, разбирать текстовые задания, анализировать изображения и собирать карточки. Интегрировать языковые и мультимодальные модели, сервисы сегментации и генерации изображений.

• 5+ лет практического опыта в ML/AI. • 2+ года в архитектуре или роли Tech Lead.

5+ лет опыта разработки на Python.

Обязанности: выполнение индивидуальных технических заданий в направлении AI-разработки (AI-продукты для бизнеса, автоматизация бизнес-процессов).

Разработка платформы для создания автономных AI-агентов разработчиков. Разработка и внедрение мультиагентных пайплайнов для автономизации SDLC.

— Создавать персонажей, окружение и key art с помощью AI; — Курировать AI-художников, давать фидбек и контролировать качество;

Allen Control Systems is looking for a Director of Computer Vision and Machine Learning to lead perception and tracking strategy, manage teams, and deliver production computer vision and machine learning systems.

- 2+ years building with large language models in production.

Location: Ukraine; North Macedonia; Turkey; European Union; Serbia; Bosnia; Georgia Workplace: Remote ABOUT US Ruby Labs is a leading tech company that creates and operates innovative consumer products. We offer a diverse range of opportunities across the health, education, and entertainment industries. Our innovative teams are driving the future of consumer-led products, and we're always looking for passionate individuals to join us. Learn more about our story at: https://rubylabs.com/about-us/ ABOUT THE ROLE We are looking for a Senior AI Engineer to own and scale the AI layer of one of our core D2C subscription products. You will be fully responsible for production LLM features and the browser automation built around them end to end — prompt systems, structured outputs, evaluation, observability, and model selection — from first experiment to live release, with quality, reliability, and cost as your accountability. This is a high-impact role suited for someone who decides with data, not intuition. Unmeasured prompt changes, untraced failures, and model swaps without benchmarks are not acceptable. You work in a modern TypeScript stack — Next.js, Cloudflare Workers and Containers with Hono, Hatchet task queues, Drizzle on Supabase Postgres, Vercel Blob. Browser automation on Browserbase and Playwright is roughly half of the job. KEY RESPONSIBILITIES PROMPT SYSTEMS & STRUCTURED OUTPUTS - Design dynamic prompt templates with conditional logic and context injection that maximise generation quality - Enforce predictable outputs with JSON mode, function calling, Zod/JSON schemas, validators, and repair loops - Own complex LLM workflows (LangChain, LlamaIndex, or custom) that integrate cleanly into application logic BROWSER AUTOMATION - Build and maintain browser automation on Browserbase Functions and Playwright that traverses web flows reliably - Classify screens with a model inside each traversal, and decide what the model handles versus deterministic code - Ship automations as frozen, published workers — versioned, reproducible, and safe to roll back - Orchestrate runs through Hatchet with retries, timeouts, and failure traces that explain every broken run EVALUATION & EXPERIMENTATION - Build evaluation pipelines — test datasets, LLM-as-a-judge, RAGAS-style metrics — and score responses and screen classifications in Langfuse - Trace complex LLM chains to find bottlenecks in cost, latency, and context-window usage - Run A/B experiments across models and prompts through an AI gateway (OpenRouter, Cloudflare AI Gateway); release only on quantitative benchmarks - Re-evaluate models as new architectures emerge; fine-tune when domain requirements demand it PRODUCTION OWNERSHIP - Take AI features from experiment to live production on Cloudflare Workers and Containers, and stay accountable after release - Manage rate limits, fallbacks, and model cost so features stay reliable at scale - Resolve production incidents in owned AI and automation systems with documented root-cause analysis QUALIFICATIONS MUST-HAVE EXPERIENCE - 【5+】 years of software engineering with Node.js, TypeScript, Next.js, and Postgres, including edge or serverless runtimes such as Cloudflare Workers - Production browser automation with Playwright (Browserbase or similar): resilient selectors, retries, failure handling at scale - Production experience with dynamic prompting — content that depends on input variables and injected context - Structured outputs in production: JSON mode, function calling, Zod/JSON schemas - Experience with unified LLM APIs or AI gateways (OpenRouter, Cloudflare AI Gateway): rate limits, fallbacks, cost-effective model selection - LLM observability with Langfuse or similar: tracing, test datasets, scoring integration - Evaluation methodology: RAGAS or custom LLM-as-a-judge systems LEADERSHIP ATTRIBUTES - Decides on benchmarks and trace data, not intuition - Analytical — converts generation logs into metrics a business can act on - Iterative — builds feedback loops and improves continuously - Owns the outcome from experiment to production, and after - Verifies before trusting — treats LLM output as unproven until validated LOCATION Ruby Labs operates within the CET (Central European Time) zone. Applicants from any country are welcome to apply for the position as long as they are located within approximately ± 4 hours of CET. This ensures optimal collaboration and communication during working hours. BENEFITS Discover the perks of being part of our vibrant team! We offer: - Remote Work Environment: Embrace the freedom to work from anywhere, anytime, promoting a healthy work-life balance. - Unlimited PTO: Enjoy unlimited paid time off to recharge and prioritize your well-being, without counting days. - Paid National Holidays: Celebrate and relax on national holidays with paid time off to unwind and recharge. - Company-provided MacBook: Experience seamless productivity with top-notch Apple MacBooks provided to all employees who need them. - Flexible Independent Contractor Agreement: Unlock the benefits of flexibility, autonomy, and entrepreneurial opportunities. Benefit from tax advantages, networking opportunities, reduced employment obligations, and the freedom to work from anywhere. Read more about it here: https://docs.google.com/document/d/1nkrN76JlZkbKj9WSOhlT1_mni_CZeDkHdwfIjPXVwvk/preview?tab=t.0#heading=h.ndsdl4wapxtt Be part of our fast-growing team and seize this excellent opportunity for personal and professional growth! INTERVIEW PROCESS After submitting your application, we conduct a thorough review which typically takes 3 to 5 days, but may occasionally take longer due to the volume of applications received. If we see a potential fit, we proceed with the following steps: - Recruiter Screening (40 minutes) - Technical Interview (60 minutes) - Final Interview (30 minutes) LIFE AT RUBY LABS At Ruby Labs, we move fast, aim high, and expect the same from our team. We’re not here to play small—we’re here to build, grow, and win. That means we look for people who are ambitious, driven, and ready to give their best every single day. This is a place for individuals who thrive under pressure, embrace challenges, and see opportunity in every obstacle. If you’re hungry to achieve, motivated by impact, and want to grow at the speed of your own ambition, Ruby Labs offers the platform to make it happen. Here, effort is matched with reward. We recognize those who go all in and deliver results, and we create space for people who want more—more responsibility, more growth, and more success. #LI-Remote

Location: New York City; US Remote Workplace: Hybrid ABOUT PINECONE Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable. ABOUT THE TEAM AND ROLE We're looking for an Applied AI Engineer who loves building real applications with AI. You'll work across the stack, from backend services and retrieval pipelines to APIs and user-facing applications, turning new AI capabilities into working solutions. This is a hands-on engineering role for someone who enjoys moving quickly, experimenting with emerging technologies, and owning projects from initial idea to production. You'll work closely with our engineering and product teams, as well as customers and partners, to explore new use cases, build reference applications, and demonstrate what's possible with Pinecone's technology. The ideal candidate combines strong full-stack engineering skills with practical experience building LLM-powered applications and agentic systems. You should be equally comfortable discussing architecture, writing production code, and putting together a working prototype. RESPONSIBILITIES - Design, build, and ship end-to-end AI applications using Pinecone’s retrieval and knowledge infrastructure. - Develop full-stack solutions spanning frontend interfaces, backend services, APIs, data pipelines, and LLM integration. - Build reference applications, integrations, and reusable components that help developers and customers adopt Pinecone. - Experiment with emerging AI patterns, including RAG, agents, tool use, context engineering, and agent memory. - Work with customers, partners, and internal teams to understand real-world problems and translate them into working software. - Evaluate and improve the quality, reliability, latency, and cost of AI-powered applications. - Share technical insights and best practices through code, examples, and technical content. - Bring learnings from building applications back into Pinecone’s product and engineering teams. WHAT YOU’LL BRING TO THE TABLE You don't need to check every box, but you should enjoy building software and be excited about what AI makes possible. FULL-STACK ENGINEERING - Strong software engineering background with experience designing, building, and shipping production applications. - Proficiency in Python and/or TypeScript, including modern backend frameworks and frontend technologies such as React or Next.js. - Experience building APIs, integrating external services, and working with databases and cloud infrastructure. - Ability to independently take a project from rough requirements through implementation and deployment. APPLIED AI - Hands-on experience building applications using LLMs, embeddings, vector databases, or retrieval-augmented generation. - Familiarity with modern AI development tools, frameworks, and APIs. - Understanding of the practical challenges of building AI applications, including retrieval quality, evaluation, latency, reliability, and cost. - Curiosity about emerging patterns in agentic applications, context management, and AI-driven workflows. OWNERSHIP & COLLABORATION - A builder's mindset: you enjoy writing code, experimenting, and getting working software into users’ hands. - Comfortable working with ambiguous requirements and making pragmatic technical decisions. - Ability to communicate technical ideas clearly to engineers, customers, and other stakeholders. - Comfortable moving between rapid prototypes and production-quality implementations. - Interest in understanding how developers and customers use the technology and translating that feedback into better solutions. BONUS POINTS - Experience with Pinecone or other vector databases and search technologies. - Experience building agentic applications, agent memory systems, or complex RAG pipelines. - Contributions to open-source projects, developer tools, or technical communities. - Experience working directly with customers on technical projects. - Experience deploying and operating AI applications in production. PERKS & BENEFITS - Comprehensive health coverage including medical, dental, vision, and mental health resources - 401(k) Plan - Equity award - Flexible time off - Paid parental leave - Annual Company Retreat - WFH Equipment Stipend Benefits and eligibility may vary by country of employment.

Чем предстоит заниматься По проекту: – Встраивать языковую модель в чат пациента (включая мессенджер), кабинет специалиста и аналитические панели: потоковая выдача, таймауты, ошибки, показ источников. – Вести библиотеку промптов и инструментов (function calling) для разных ролей, с версионированием и регрессионными проверками.

• Спроектировать и собрать автономного ИИ-агента под конкретную бизнес-задачу. • Настроить агенту вызов функций (API, базы данных, CRM), чтобы он умел выполнять действия, а не просто общаться.

— Develop AI-based software solutions for the legal sector. — Automate complex legal workflows end-to-end.

✔️ 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 Jersey; New York; Pennsylvania; Connecticut; Massachusetts Workplace: hybrid 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 long wait for impact of a firm with a hundred thousand people. 350+ builders, 100+ customers in production, led by our founders 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 augmentation. 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, with 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. 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 nondeterministic 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 Presales 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 once a week Unlimited Vacation policy Generous health, vision, and dental insurance 401(k) matching plan Base salary $180k to $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, Cofounder & 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.

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.

🚀 The Adventure Ahead As a founding member of our Forward Deployed Engineering (FDE) team, you will bridge the gap between cutting-edge AI technology and real-world impact. You will work hand-in-hand with our most forward-thinking, strategic customers to transform complex L&D workflows into autonomous, high-impact AI agents.