- Design and build AI coding agents for feature development, bug fixing, testing, code review, documentation, and engineering automation
- Create specification-driven workflows that transform requirements into implementation plans, code changes, tests, and technical documentation
- Develop multi-agent systems involving planning, development, review, testing, and validation agents
- Implement codebase understanding, repository navigation, dependency analysis, tool calling, memory, and task decomposition
- Integrate agents with GitHub or GitLab, Jira, CI/CD pipelines, IDEs, APIs, and other engineering tools
- Build and integrate MCP servers and tools, as well as A2A communication
- Develop Python-based orchestration services and integrate them with .NET applications and enterprise platforms
- Automate unit, functional, regression, and code-quality testing
- Establish agent evaluation and observability covering task completion, code quality, test results, hallucinations, costs, and execution traces
- Implement secure execution environments, permissions, human approvals, and guardrails for autonomous agents
- Strong hands-on software engineering experience with Python or .NET/C#
- Experience building GenAI applications, agentic systems, or AI coding assistants
- Solid knowledge of software architecture, SDLC, code generation, testing, debugging, and CI/CD
- Experience with LangGraph, OpenAI Agents SDK, Semantic Kernel, AutoGen, CrewAI, or similar frameworks
- Strong understanding of MCP, A2A, tool calling, agent memory, workflow execution, and multi-agent orchestration
- Experience connecting LLMs with source-code repositories, developer tools, APIs, and enterprise knowledge bases
- Proficiency with Git, GitHub or GitLab, Docker, Kubernetes, and cloud-native development
- Experience with observability and evaluation tools such as Langfuse, OpenTelemetry, LangSmith, MLflow, or Phoenix
Nice to have
- Experience building autonomous software engineering agents or internal developer platforms
- Knowledge of specification-driven development, story-to-code automation, test generation, and automated code validation
- Experience creating reusable engineering productivity tools or AI-powered SDLC platforms
- Familiarity with enterprise SaaS, AWS, RAG, knowledge graphs, and large-scale codebase analysis
We are looking for a Lead Agentic AI Developer to design and build enterprise-grade coding agents and AI-powered software development automation.
In this hands-on role, you will create intelligent agents capable of understanding requirements, navigating complex codebases, planning and implementing changes, generating tests, reviewing code, troubleshooting issues, and automating engineering workflows across the SDLC.
- EDU corporate community (300+ members): tech communities, interest clubs, events, a small R&D lab, a knowledge base, and a dedicated AI track
- Licenses for AI tools: GitHub Copilot, Cursor, and others
- Expanded medical support for employees in Tashkent
- 19 working days of vacation per year, 21 after two years in the company
- Corporate getaway & teambuilding activities
- Support for the significant events in your life
- Referral bonuses for bringing in new talent