Senior AI Engineer (Agentic Systems & Python)
We are seeking a highly skilled Senior AI Engineer to join our strategic R&D initiative, "GAIN core." The primary objective of this project is to develop an automated, AI-driven estimation system that transforms how software development projects are scoped. By turning days of manual estimations into precise, data-driven insights within hours, this project will lay the architectural foundation for a future enterprise SaaS platform.
Essential functions
- Agentic Architecture: Design, build, and debug long-running, multi-phase agentic pipelines using Python (FastAPI, asyncio, FastMCP) and advanced LLM APIs (e.g., Anthropic API, Claude-Agent-SDK).
- MCP Integration: Implement Model Context Protocol (MCP) servers, expose tools, and ensure seamless integration with clients.
- Multi-Agent Orchestration: Manage parallel agent execution, workspace isolation, and sandboxed environments via advanced prompt engineering.
- Cloud & CI/CD Delivery: Create Infrastructure as Code (IaC) definitions, build CI/CD pipelines (GitHub Actions), and deploy containerized applications on GCP (GKE, Cloud Firestore) or AWS using Kubernetes.
- ML Monitoring & Evaluation: Implement rigorous evaluation and monitoring processes to validate ML/AI system outputs against real-world data.
Qualifications
- Python Expertise: Extensive commercial experience in backend development using modern Python (FastAPI, asyncio).
- Agentic AI & LLMs: Proven track record of designing multi-agent systems, working with LLM APIs/SDKs, and applying complex prompt engineering.
- MCP Knowledge: Practical understanding of Model Context Protocol, hooks, skills, tools, and agents.
- Cloud & DevOps: Strong proficiency in GCP (or AWS), Kubernetes, Docker (multi-stage builds), and automated CI/CD pipelines.
- AI Tooling: Familiarity with AI-assisted coding tools (e.g., Claude Code, Cursor, OpenCode) and a deep understanding of AI coding best practices.
Would be a plus
- Experience with LLM evaluation frameworks (LLM-as-Judge) and ML Ops / LLM Ops (prompt versioning, A/B testing).
- Knowledge of code complexity metrics and static analysis tools (e.g., AST, git-based complexity analysis, P10Y/Compass).
- Experience with Pydantic v2, schema-driven API design, and OAuth/OIDC integration.
- Background in building developer tools, SDKs, or IDE integrations.
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.