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Location: Chicago, IL or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As a Senior AI Engineer you will own LLM-powered systems and agentic workflows for our customers. These systems automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with a measured accuracy you can defend as models change and usage grows. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system architecture, code quality, security, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the eval bar it ships against. Salary range is: $180,000 - 225,000 This position is bonus eligible. Key Responsibilities: Own the delivery of LLM-powered systems in Python and TypeScript, from an ambiguous customer problem, scoped with product managers and data scientists, through production operation. Set the evals and guardrails strategy for your area: what gates a release, what production signals the team watches, and how a change is simulated against historical claims before it ships. Raise the bar for how the team works with agentic coding tools: sharpen the specifications, instruction files, hooks, and permission policies they run under, and hold generated code to the same review standard before it merges. Design the NLP pipelines that turn unstructured claim data into structured data customers can act on, choosing where semantic search, classical NLP, or an LLM fits. Build and operate durable, event-driven, multi-tenant systems in which agents run as steps inside deterministic workflows, designing their failure modes, replay semantics, and cost profile before they show up under load. Own tracing and audit for your area: every model call and agent step recorded, so any recommendation can be reconstructed and cited back to its sources by on-call and auditors alike. Set the privacy and security baseline every system in your area starts from: tenant isolation, least-privilege access for agents and their tools, redaction, retention, and what data may reach a model provider. Author the design documents for complex systems to get feedback and buy-in, review other engineers' designs and code with the same care, and mentor the engineers in your area. Take part in a shared on-call rotation for the systems you own. Requirements: 6+ years of professional software engineering experience, including an LLM-powered system you architected, shipped to external customers, and carried through at least one model or prompt migration. Python and TypeScript at the level of setting a team's conventions: the async model, typing strictness, and test strategy for a shared codebase, plus a performance problem you profiled and fixed. An evals and guardrails strategy you set for a product area others built in: where human approval was required, and how production corrections re-entered the evals. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work, plus changes you turned back, and why. Pipelines you designed that blend LLMs, semantic search, and classical NLP, including a retrieval design you can defend and a case where a classical technique beat an LLM on cost, latency, or reliability. Durable, event-driven systems you designed with deterministic orchestration around non-deterministic model steps: compensating actions, idempotency, backpressure, and event-sourced replay. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Systems architected and operated on Azure or AWS, with CI/CD and infrastructure as code, and hands-on time with a durable workflow engine such as Temporal or the Durable Task Scheduler. Technical design documents you have authored for systems that span more than one team, used to get feedback and buy-in before building, and that those teams then built to. Clear writing and discussion for technical and non-technical audiences: drawing out a customer's real problem and explaining the trade-offs back to them. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences. Experience with agent frameworks, LangGraph, PydanticAI, and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing. Experience designing A/B tests for AI features. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months, every model change in your area is gated by evals you designed, regressions are caught before a customer sees them, and you can show the accuracy number held or moved. You are trusted with the high-stakes, ambiguous problems, and you turn them into a roadmap, a shipped system, and a number you can put in front of a customer. You are energized by what agentic coding tools make possible. Your team ships more than its headcount suggests, and your specifications and reviews are why the output survives production. You have a passion for systems that last: the ones you design have their failure modes understood in advance, and when one fails anyway, the trace says exactly where. Privacy and security reviews of systems in your area find nothing that was not already designed in. Standards you set for evals, reviews, and design documents outlive the project they started on. Engineers you mentor ship LLM-powered features with evals and guardrails in place without your direct involvement. You enjoy getting a product manager, a data scientist, and a customer's team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Location: Chicago, IL or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As an AI Engineer you will build and ship LLM-powered features and agentic workflows for our customers. These features automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with measured accuracy, not a convincing demo. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system design, security, and hard debugging. You own features end to end. Salary range is: $170,000 - 195,000 This position is bonus eligible. Key Responsibilities: Ship LLM-powered features and agentic workflows in Python and TypeScript, from a problem scoped with product managers and data scientists through production traffic, and help set the metrics you will be measured against. Write the evals, guardrails, and feedback loops that make your features trustworthy, and hold them to explicit token and latency budgets. Use agentic coding tools every day, and own the review of what they produce: catch the correctness, security, and design problems in generated code before you open the pull request. Maintain and extend the NLP pipelines that turn unstructured claim data into structured data customers can act on, blending semantic search, classical NLP, and LLMs. Build and operate durable, event-driven services in which agents run as steps inside deterministic workflows, with checkpointed model outputs so a retry does not re-invoke a completed LLM step. Trace every model call and agent step so a recommendation can be reconstructed and audited, with citations back to the source documents, and wire that tracing into your alerts. Model and query claims data across relational, document, and graph stores. Design privacy and security in from the start: tenant isolation, least-privilege access for agents and their tools, and a clear rule for what data may reach a model provider. Write a technical design document before any significant change, and use it to get feedback and buy-in from the team before you build. Take part in a shared on-call rotation for the services you build. Requirements: 3+ years of professional software engineering experience, including at least one LLM-powered feature you shipped and then operated in production. Python and TypeScript: typed, tested, async code in both, and real depth in one. Evals you have designed for LLM output, plus guardrails you have shipped. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work. Pipelines that blend LLMs with semantic search and classical NLP: structured output, tool calling, embedding-based retrieval, and a case where a classical technique beat an LLM. Services built on message- or event-driven architectures, including long-running workflows with retries, idempotent handlers, and event-sourced state, plus an LLM or agent step you ran inside one. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Backend services built and operated on Azure or AWS, and exposure to a durable workflow engine such as Temporal or the Durable Task Scheduler. Technical design documents you have written to get feedback and buy-in from a team before building, and that the team then built to. Clear writing and discussion for technical and non-technical audiences, and code review you can give as well as take. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end. Chat, streaming, and citation-heavy AI experiences especially. Experience with CI/CD pipelines and infrastructure as code such as Terraform or Bicep. Experience with agent frameworks, LangGraph and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing. Experience designing A/B tests for AI features, or what-if simulations that replay historical claims through a proposed change before it ships. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months you ship an LLM-powered feature, its evals run in CI, and you can name the metric it moved. When a model migration or prompt change causes a regression, the evals you wrote catch it before a customer does. You take ownership from concept to production with light direction, asking the right questions early. You care that things hold up: the services you build survive retries, partial failures, and model migrations without incidents a customer can see. When something goes wrong in production, the trace tells you which step and which model call, and you can show an auditor the same thing. Privacy and security reviews of your features find nothing that was not already designed in. You enjoy the craft, and it shows: engineers pick up your patterns without being told to. You enjoy the back-and-forth that gets a feature scoped, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Location: Islamabad, Pakistan Workplace: hybrid We are looking for a Senior Software Engineer to build and run backend services and internal web applications for our AI teams. You will write production-grade Go, Python and TypeScript , own your services from design to on-call. You bring hands-on experience building AI agents in production: tool calling, state, reliability and observability of LLM-based systems. You will work with data scientists, backend engineers, QA and product managers. Key Responsibilities Design, build and run backend services in Go and Python, and own them in production: delivery, monitoring, on-call. Build and evolve backend services that run LLM-based agents: tool calling, MCP integrations, structured output, conversation state and guardrails in code. Build internal web applications in React and TypeScript, from simple admin pages to complex interactive interfaces. Support and develop existing production services together with the team: reviews, on-call, fixes and new features. Design data models and APIs for configuration-heavy products, with attention to consistency, history and safe changes. Integrate services with the wider backend: sync (HTTP, gRPC, GraphQL) and async (Kafka) communication, built for reliability. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Drive technical research and design for new features. Weigh trade-offs and write them down. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial software engineering, with production work on both backend and frontend . You have written production code without coding agents. Strong Go: you know and have used its advanced features in production. Strong Python for service code: async, typing, testing, and a modern web framework such as FastAPI. Hands-on experience building and running AI agents in production Strong TypeScript and React: you have built and maintained non-trivial web applications, including complex forms, editors and data visualisation. Strong SQL: schema design, indexes, query optimisation and migrations. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, GraphQL, Kafka), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, OpenTelemetry or similar). Git workflows and code review, comfortable Linux command line, and networking basics. Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Experience using AI coding agents with full review of generated changes. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Almaty, Kazakhstan Workplace: hybrid We are looking for a Senior Software Engineer to build and run backend services and internal web applications for our AI teams. You will write production-grade Go, Python and TypeScript , own your services from design to on-call. You bring hands-on experience building AI agents in production: tool calling, state, reliability and observability of LLM-based systems. You will work with data scientists, backend engineers, QA and product managers. Key Responsibilities Design, build and run backend services in Go and Python, and own them in production: delivery, monitoring, on-call. Build and evolve backend services that run LLM-based agents: tool calling, MCP integrations, structured output, conversation state and guardrails in code. Build internal web applications in React and TypeScript, from simple admin pages to complex interactive interfaces. Support and develop existing production services together with the team: reviews, on-call, fixes and new features. Design data models and APIs for configuration-heavy products, with attention to consistency, history and safe changes. Integrate services with the wider backend: sync (HTTP, gRPC, GraphQL) and async (Kafka) communication, built for reliability. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Drive technical research and design for new features. Weigh trade-offs and write them down. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial software engineering, with production work on both backend and frontend . You have written production code without coding agents. Strong Go: you know and have used its advanced features in production. Strong Python for service code: async, typing, testing, and a modern web framework such as FastAPI. Hands-on experience building and running AI agents in production Strong TypeScript and React: you have built and maintained non-trivial web applications, including complex forms, editors and data visualisation. Strong SQL: schema design, indexes, query optimisation and migrations. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, GraphQL, Kafka), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, OpenTelemetry or similar). Git workflows and code review, comfortable Linux command line, and networking basics. Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Experience using AI coding agents with full review of generated changes. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Cairo, Egypt Workplace: hybrid We are looking for a Senior Software Engineer to build and run backend services and internal web applications for our AI teams. You will write production-grade Go, Python and TypeScript , own your services from design to on-call. You bring hands-on experience building AI agents in production: tool calling, state, reliability and observability of LLM-based systems. You will work with data scientists, backend engineers, QA and product managers. Key Responsibilities Design, build and run backend services in Go and Python, and own them in production: delivery, monitoring, on-call. Build and evolve backend services that run LLM-based agents: tool calling, MCP integrations, structured output, conversation state and guardrails in code. Build internal web applications in React and TypeScript, from simple admin pages to complex interactive interfaces. Support and develop existing production services together with the team: reviews, on-call, fixes and new features. Design data models and APIs for configuration-heavy products, with attention to consistency, history and safe changes. Integrate services with the wider backend: sync (HTTP, gRPC, GraphQL) and async (Kafka) communication, built for reliability. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Drive technical research and design for new features. Weigh trade-offs and write them down. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 5+ years of commercial software engineering, with production work on both backend and frontend . You have written production code without coding agents. Strong Go: you know and have used its advanced features in production. Strong Python for service code: async, typing, testing, and a modern web framework such as FastAPI. Hands-on experience building and running AI agents in production Strong TypeScript and React: you have built and maintained non-trivial web applications, including complex forms, editors and data visualisation. Strong SQL: schema design, indexes, query optimisation and migrations. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, GraphQL, Kafka), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, OpenTelemetry or similar). Git workflows and code review, comfortable Linux command line, and networking basics. Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Experience using AI coding agents with full review of generated changes. Why join us Help us challenge injustice by creating fair choices for millions of people across 47 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Проводить анализ безопасности архитектуры, выявлять угрозы и уязвимости, связанные с использованием AI-агентов/LLM/GenAI во внутренних и внешних продуктах компании. Разрабатывать требования безопасной разработки в сфере использования AI-агентов/LLM/GenAI.

Develop and maintain backend services with C# and .NET. Develop and maintain frontend logic with Angular and Redux.

• Опыт системного анализа IT-проектов от 3 лет. • Опыт описания бизнес-процессов в Confluence.

• ML Engineer, middle 1 Опыт деплоя ML-моделей от 2 лет. • Опыт с очередями, написание прод кода для агентов.

Location: Москва Мы команда ФинСтрой AI, которая разрабатывает ИИ-решения для прогнозирования стоимости объектов строительства СБЕРа. Наша задача сократить срок подготовки оценки объекта строительства и повысить её точность. Ищем AQA-инженера, который будет тестировать поведение агента, интеграции и пользовательские сценарии. Обязанности ### **Задачи:** * формировать и поддерживать тестовую модель продукта совместно с аналитиками и разработчиками * формировать тестовые корзины для детерминированных и недетерминированных сценариев агента: входные данные, источники, ожидаемый результат и критерии проверки * формировать нагрузочный профиль агента * описывать модель поведения агента в основных, альтернативных и негативных сценариях * разработка автотестов по тест-кейсам * проводить функциональное, интеграционное, регрессионное и исследовательское тестирование web-интерфейса, backend и API * проверять корректность расчётов, полноту и непротиворечивость результата, актуальность данных, наличие обоснований и ссылок на источники * разбирать логи и трайсы работы агента, локализовывать ошибки на уровне модели, интеграции, данных или тестового стенда * тестировать сценарии с отсутствующими или противоречивыми данными, ошибками API, тайм-аутами и недоступностью внешних сервисов * заводить и сопровождать дефекты, поддерживать тестовую документацию и участвовать в подготовке релизов. Требования ### **Мы ожидаем** * опыт коммерческого тестирования web и backend-систем от трех лет * опыт автоматизации тестирования на Python, Java или TypeScript с использованием Pytest, Requests, Playwright, Selenium или аналогов * знание теории тестирования и практический опыт применения техник тест-дизайна * опыт тестирования ИИ-решений, RAG-систем или продуктов с использованием LLM * опыт тестирования REST API и интеграций * навыки работы с JSON, Postman или curl, DevTools и логами * понимание клиент-серверной архитектуры и базовых принципов работы микросервисов * умение составлять тест-кейсы, чек-листы и понятные отчёты о дефектах * готовность тестировать сценарии с вариативным результатом, выполнять повторные прогоны и сравнивать результаты с заданными критериями * умение уточнять требования и взаимодействовать с аналитиками, разработчиками и бизнес-экспертами **Будет плюсом:** * опыт проведения нагрузочного тестирования * опыт создания eval-наборов или автоматизированных проверок результатов работы ИИ-систем * опыт тестирования тулов и MCP-серверов: контрактов, схем, авторизации, тайм-аутов, повторных вызовов и обработки ошибок * опыт тестирования финансовых, аналитических, банковских или строительных систем. Условия ### Мы предлагаем: * ежегодный пересмотр зарплаты, годовой бонус * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * ипотека для сотрудников выгоднее до 4% * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера корпоративная пенсионная программа.

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Location: Ukraine Workplace: remote Creatio is an AI CRM and workflow platform where people and AI agents work together — with no limits on users, agents, or scale. We help midsize and large organizations run customer workflows in the AI era. With a global team and a large ecosystem of partners, Creatio serves thousands of customers in over 100 countries and automates tens of millions of workflows daily. Genuine care for our clients and partners is at the heart of our DNA.We’re proud to be recognized by top industry analysts as a Leader and Strong Performer in multiple Gartner and Forrester reports. In 2025, Creatio was named to Inc.’s Best Workplaces list, recognizing our commitment to employee wellbeing and a strong workplace culture.Who We’re Looking For:We are looking for an experienced AI Tech Lead with a strong .NET engineering background and hands-on expertise in building production-grade AI solutions.In this role, you will lead the technical direction of an AI engineering team responsible for designing, developing, and operating intelligent capabilities within the Creatio platform.You will work on the AI agent platform that enables AI agents to safely perform real work within enterprise workflows — interacting with tools and APIs, accessing business data, maintaining context and memory, enforcing permissions, and collaborating with humans when needed.This is a hands-on technical leadership role that combines software architecture, advanced AI engineering, team mentorship, and active involvement in development.We are looking for someone who can make architectural decisions, solve complex engineering challenges, introduce modern AI development practices, and help the team deliver reliable, secure, and scalable AI-powered solutions.Responsibilities:Lead the development of architectural solutions, including AI-powered features, agentic workflows, RAG-based solutions, and LLM integrations.Drive continuous optimization of development processes; introduce modern tools, AI-assisted development practices, engineering standards, and quality improvements.Facilitate team ceremonies: backlog refinements, sprint planning, and sprint reviews (demos).Take an active part in backlog execution: pair programming, complex development, code reviews, and mentoring.Collaborate closely with stakeholders and product managers to define technical direction and translate business requirements into technical solutions.Guide the design and implementation of AI agent architectures, including tool calling, orchestration, context and memory management, permissions, and guardrails.Ensure high quality through automated testing, AI evaluations, observability, and continuous monitoring of production AI solutions.Monitor and guide incident response (4th-line support), ensuring SLA compliance and issue resolution.Actively contribute to knowledge sharing, team development, and continuous improvement.Requirements: Must have:6+ years of professional software engineering experience, with strong expertise in C# and .NET.3+ years of experience in a Tech Lead or Team Lead role, including architectural decision-making, technical ownership, and mentoring.Hands-on experience building and delivering LLM-powered applications to production.Strong understanding of AI agent architectures, including tool calling, orchestration, context management, and agent frameworks.Knowledge of prompt engineering, AI evaluations, observability, and AI security best practices.Proficiency with AI coding agents (Claude Code, Cursor, Codex, or similar tools) in daily development.Strong knowledge of software architecture, distributed systems, REST APIs, and backend engineering principles.Experience with relational databases, automated testing, CI/CD, and cloud-native development.English level: Upper-Intermediate or higher, with strong communication, leadership, and problem-solving skills.Nice to have:Experience with MCP, multi-agent systems, and advanced agent orchestration.Practical experience with RAG, embeddings, vector/hybrid search, and LLM integrations.Knowledge of LLMOps practices, including evaluation pipelines, monitoring, and cost optimization.Experience with AI platforms such as Anthropic API, Azure OpenAI, AWS Bedrock, or Google Vertex AI.Python experience for AI development, prototyping, or automation.Experience with Kubernetes, enterprise SaaS products, or low-code/no-code platforms.What to expect from us:Growth & Development: Clear career paths, mentorship opportunities, and access to continuous learning to help you reach your full potential.Flexibility & Well-Being: We provide flexible work arrangements and initiatives that empower you to manage your schedule effectively, stay productive, and thrive both personally and professionally.Recognition & Impact: A culture that celebrates achievements, values your ideas, and empowers you to make real contributions from day one.Innovative Culture: Be part of a company that embraces new ideas, modern technologies, and bold thinking to stay ahead of the curve.Benefits & Rewards Package: We provide competitive compensation and benefits designed to support you and your family. Our rewards approach goes beyond salary, recognizing your contributions and commitment. The exact package may vary depending on your country of residence and employment type.

Location: Intellias Meet your recruiter Diana Meneses diana.meneses@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Python Engineer Senior Argentina, Chile, Colombia, Costa Rica, Mexico Remote APPLY NOW REFER A FRIEND We are looking for a Senior Python Backend Engineer who is passionate about applying modern AI-assisted software development practices to build secure, scalable healthcare platforms. Beyond strong backend engineering skills, we are looking for someone who actively leverages AI development tools, LLM-powered workflows, and automation to improve engineering productivity, code quality, and delivery speed. You will work on a modern healthcare interoperability platform while collaborating with an engineering team embracing AI-first development practices and cloud-native technologies. What project we have for you The platform enables secure access, exchange, and processing of clinical healthcare data across providers, healthcare organizations, and patients using modern interoperability standards including FHIR. The engineering team embraces AI-assisted software development, modern cloud-native architecture, and automation-first engineering practices. Engineers are encouraged to use AI tools to improve software quality, accelerate development, automate repetitive tasks, and increase engineering productivity. You will contribute to backend services powering healthcare interoperability while helping evolve the team’s AI-native engineering practices. What you will do Design, develop, and maintain scalable backend services using Python, FastAPI, and asynchronous programming principles. Build high-performance APIs and microservices that support secure healthcare data exchange and interoperability. Design, implement, and optimize MongoDB data models and persistence layers for high-volume production workloads. Develop integrations with healthcare systems, identity providers, cloud storage platforms, and external service providers. Implement secure authentication and authorization mechanisms using OAuth 2.0, OpenID Connect (OIDC), and JWT. Build and enhance backend services supporting healthcare interoperability standards, including FHIR-based integrations. Leverage AI-powered development tools and engineering assistants to accelerate software delivery while maintaining high standards of code quality, security, and maintainability. Collaborate with architects and engineering teams to identify opportunities for applying AI-assisted development practices and modern engineering workflows. Participate in technical design discussions, architecture reviews, and technology selection decisions. Write clean, well-tested, and maintainable code following modern software engineering best practices. Develop and maintain automated unit, integration, and end-to-end tests to ensure platform reliability. Troubleshoot complex production issues, perform root cause analysis, and implement sustainable solutions. Contribute to platform observability, monitoring, performance optimization, and operational excellence. Participate in code reviews, mentor fellow engineers, and promote engineering best practices across the team. Continuously evaluate emerging technologies, AI engineering tools, and modern development practices to improve engineering productivity and product quality. What you need for this Requirements: 5+ years of professional software engineering experience developing backend applications in production environments. Strong proficiency in Python (3.11/3.12+) and modern backend development practices. Hands-on experience building high-performance asynchronous applications using FastAPI and Python async/await. Solid understanding of RESTful API design, distributed systems, and microservice architecture. Experience working with MongoDB in production environments; familiarity with Beanie ODM or similar asynchronous ODM frameworks. Strong knowledge of authentication and authorization technologies, including OAuth 2.0, OpenID Connect (OIDC), JWT, and modern Identity Providers. Experience developing, debugging, and deploying containerized applications using Docker and Docker Compose. Strong understanding of software architecture, scalability, reliability, and performance optimization. Experience writing automated tests using Pytest and applying modern software quality practices. Familiarity with CI/CD pipelines and modern DevOps workflows. Strong analytical, troubleshooting, and debugging skills. Excellent communication skills and ability to collaborate effectively within cross-functional Agile teams. Proven experience using AI-assisted software development tools to improve engineering productivity, software quality, and development velocity. Hands-on experience with one or more AI coding assistants such as GitHub Copilot, Cursor, Claude Code, ChatGPT, Windsurf, or similar. Ability to effectively leverage Large Language Models (LLMs) for code generation, debugging, refactoring, documentation, test generation, and architectural exploration while maintaining high engineering standards. Experience reviewing, validating, and improving AI-generated code with strong engineering judgment. Experience developing healthcare interoperability solutions or working within Digital Health platforms. Knowledge of healthcare interoperability standards, including: HL7 FHIR R4 SMART Health Links (SHL) SMART Health Cards (SHC) Nice to have: Experience building secure clinical data exchange pipelines and healthcare integration workflows. Familiarity with JWE encryption/decryption mechanisms and secure healthcare data transmission. Experience with Model Context Protocol (MCP) and AI integration frameworks. Experience developing MCP servers or AI-enabled backend services. Experience integrating Large Language Models (LLMs) or AI services into enterprise applications. Knowledge of Retrieval-Augmented Generation (RAG), AI agents, or agentic application architectures. Experience integrating with external platforms and services, including: Google Drive Microsoft OneDrive Box SMTP services FHIR servers Familiarity with QR code and image decoding technologies (e.g., pyzbar, zbar). Experience with Playwright-based end-to-end testing frameworks. Knowledge of Cucumber/BDD methodologies. Experience with observability and monitoring technologies, including: OpenTelemetry Prometheus Experience working with event-driven architectures and Kafka. Experience with AWS cloud services, including AWS Secrets Manager. Exposure to TypeScript and React for occasional full-stack contributions. Experience working in regulated industries requiring strong security, privacy, and compliance practices (HIPAA, SOC 2, GDPR, or similar). Passion for adopting emerging AI engineering practices and continuously improving software development workflows. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills Python

Location: Москва Мы в поиске  Lead Python backend-разработчика, который будет управлять командой разработчиков, развивать и внедрять процессы разработки и при этом оставаться практикующим инженером: проектировать, реализовывать и развивать микросервисы, участвовать в обсуждении архитектурных решений. Агентная разработка у нас — не строчка «будет плюсом», а то, как устроена ежедневная работа команды: кодовые агенты, реестр скиллов, правила для агентов и spec-driven development. Мы строим технологическую платформу нового поколения для производства, хранения и дистрибуции медиаконтента. Это интеллектуальная экосистема, которая автоматизирует жизненный цикл материалов: от загрузки и разметки до бесшовной публикации в десятках цифровых каналов — сайты, приложения, мессенджеры, соцсети. Обязанности ### Чем предстоит заниматься: * руководить командой backend-разработчиков: планирование, декомпозиция и оценка задач, развитие инженерных процессов * решать задачи отказоустойчивости и горизонтального масштабирования * участвовать в проектировании взаимодействия сервисов: обсуждать их ответственность, API и контракты событий * разрабатывать асинхронные микросервисы на FastAPI * реализовывать обработку событий Kafka: гарантии доставки, идемпотентность, повторную обработку; применять принятые в команде решения для согласования изменений данных и публикации событий * использовать кодовых агентов для разработки, поддерживать проектные правила и скиллы, проверять и дорабатывать сгенерированный код * работать с логами и метриками, участвовать в диагностике и устранении ошибок сервисов проекта * взаимодействовать с аналитиками, QA и frontend-разработчиками. **Стек:** Python 3.12+, asyncio, FastAPI, REST PostgreSQL, Tortoise ORM / SQLAlchemy, Redis Apache Kafka FastStream, Django / Wagtail OpenSearch / Elasticsearch GigaCode CLI, реестр скиллов, AGENTS.md / rules, MCP Docker, OpenShift (Kubernetes) Jenkins, Nexus, Bitbucket, SonarQube, Jira, Confluence Требования ### Что для нас важно: ### * от 5 лет коммерческой разработки на Python и профильное IT-образование * уверенное знание Python и asyncio: асинхронный ввод-вывод, конкурентное выполнение, понимание влияния блокирующего кода * практический опыт разработки сервисов на FastAPI, реализации REST API и участия в их проектировании * опыт микросервисной разработки, реализации взаимодействия нескольких сервисов. Понимание архитектуры сервиса * уверенный SQL и PostgreSQL: транзакции, индексы, планы запросов. Опыт работы с ORM * практический опыт с Redis: кеширование, TTL и инвалидация кеша * работа с Docker, логами и метриками приложений; опыт участия в диагностике ошибок и production-инцидентов своего сервиса * практический опыт Apache Kafka в production. Понимание гарантий доставки и порядка сообщений; реализация идемпотентной обработки и защиты от дублей * опыт руководства командой разработчиков или роли техлида: постановка задач, код-ревью, развитие людей * умение выстраивать и внедрять процессы разработки в команде. **Будет преимуществом:** * паттерны проектирования: понимание и практическое применение; умение выбирать подходящий паттерн под задачу * принципы разработки и чистый код: понимание и применение SOLID и других принципов * Kafka: диагностика consumer lag и ребалансировок, версионирование событий и совместимость схем * отказоустойчивость межсервисных взаимодействий: понимание и применение * производительность: профилирование, оптимизация и нагрузочное тестирование * фреймворки и протоколы: FastStream, Django / Wagtail, SSE, gRPC * поиск: OpenSearch / Elasticsearch; векторный поиск с pgvector / Qdrant * эксплуатация: диагностика приложений в Kubernetes / OpenShift * агентские инструменты: создание собственных скиллов, опыт настройки MCP-интеграций и разработки MCP-серверов, применение SDD в командной разработке * AI-функции продукта: интеграция LLM и разработка агентов, в том числе с LangChain / LangGraph или аналогами. Условия * комфортный современный офис по адресу Кутузовская 32 или Оружейный 41 * формат работы – офис/гибрид * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

— Разработка инструментов для AI-агентов и интеграция с корпоративными системами (1С, почта, файловые ресурсы);

-Разработка инструментов для агентов и интеграций с корпоративными системами (1С, почта, файловые ресурсы). -Обработка документов: договоры, счета, таблицы.

Задачи: — Организовать процесс внедрения AI-решений от подачи заявки до поддержки. — Развивать Doc AI и автоматизацию обработки документов. — Внедрять AI-агентов, MCP-коннекторы и автоматизацию бизнес-процессов. — Руководить командой AI-инженеров. — Контролировать качество решений, метрики, SLA и ROI. — Обеспечивать внедрение LLM-решений. Требования: — Наличие практического опыта работы с LLM, RAG и AI-агентами не менее 3 лет. — Опыт управления командой и внедрения AI-решений. Условия: — Совокупный доход состоит из оклада и годового бонуса.

Location: Москва Мы в **Sber AI** ищем **Middle/Senior ML Engineer**. **Коротко о нас:** мы – молодая команда, которая тесно работает с людьми, принимающими решения большого масштаба. Делаем проекты, влияющие на то, как устроены процессы в стране и разрабатываем стратегии развития ИИ. Параллельно занимаемся AI Journey – одной из самых больших AI-конференций в мире. Обязанности * развёртывание и оптимизация локального инференса LLM: подбор моделей, квантизация, настройка производительности * оценка требований к GPU под нагрузку * построение и улучшение поиска по документам (RAG): эмбеддинги, гибридный поиск, реранкинг * дообучение моделей под задачи заказчика (LoRA, SFT) * настройка промптов, структурированного вывода и вызова инструментов для агентных сценариев * разработка агентного харнесса: цикл агента, управление контекстом и памятью, лимиты шагов, обработка ошибок инструментов, восстановление после сбоев * разработка MCP-серверов для доступа агентов к системам и данным заказчика: реестры, документооборот, базы знаний, внутренние API * настройка tool calling и структурированного вывода у локальных моделей. Требования * опыт от 3 лет в ML/NLP, из них не менее года с LLM * PyTorch, Hugging Face (transformers, PEFT) * опыт локального инференса: vLLM, SGLang * квантизация на практике: AWQ, GPTQ, GGUF, понимание компромисса между качеством и скоростью * понимание устройства инференса: KV-cache, батчинг, latency и throughput, расчёт памяти * опыт написания собственного MCP-сервера * опыт построения RAG-систем * уверенный Python, Docker на рабочем уровне Будет плюсом: * опыт fine-tuning с LoRA * работа с open-weight моделями (Qwen и аналоги) на русском языке * опыт агентных систем и tool calling. Условия * комфортный современный офис рядом с м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты. Годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.