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Job Description
Structured overview of role & requirementsAbout This Role
Define and evolve solution architecture for integration of AI agentic workflows and developer platforms (IDE, CI/CD, pull requests).
Design and deliver production-grade AI agentic workflows and integrations including APIs, servers, and multi-agent orchestration techniques.
Lead technical evolution, governance, and reliability of AI assistant tools and MCP Gateway used in secure software development.
Minimum Requirements
Significant professional software engineering experience with demonstrated technical leadership on complex, cross-team systems.
Hands-on experience building production agentic AI systems with multi-agent orchestration or comparable frameworks (e.g., LangChain, LangGraph).
At least two years of experience applying large language models (LLMs) in production workflows, including prompt engineering and API integration.
Experience with modern developer tooling such as CI/CD, Git workflows, pull request automation, and distributed systems; proficiency in one or more languages: Python, Java, or Go.
Ideal Candidate Profile
Experienced in architecting and delivering AI-integrated developer tooling or platforms, focusing on multi-agent systems and AI-assisted development workflows.
Technical leadership demonstrated by ownership of end-to-end projects involving complex integrations and cross-functional collaboration with Product and AI teams.
Prior exposure to application security or DevSecOps tooling and deep familiarity with LLM integration components like vector databases and agent observability is a plus but not mandatory.