Description

You define and evolve the architecture for the Agentic System Layer, designing multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines at production scale.

This role is hybrid.

Responsibilities

• Design scalable distributed systems using microservices and event-driven architecture, defining REST and gRPC API contracts.
• Build and improve RAG pipelines, prompt-management solutions, tool-calling patterns, and LLM-routing strategies.
• Establish enterprise patterns for agent reliability, observability, security, guardrails, and graceful degradation.
• Evaluate and integrate agentic AI frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, and AutoGen.
• Lead technical design reviews, create Architecture Decision Records (ADRs), and mentor engineers on production-grade AI practices.

Required Skills

• 10+ years of software architecture or senior engineering experience, including 3+ years designing AI/ML platform systems.
• Hands-on experience with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel) and agentic AI systems.
• Deep expertise in distributed systems, microservices, and event-driven design.
• Strong knowledge of multi-agent orchestration, agent tool-use patterns, and RAG pipelines.
• Advanced programming skills in Python.
• Proficiency in at least one additional language: Java, Go, or TypeScript.
• Strong API design experience using REST and/or gRPC.
• Bachelor's degree in a technical field.

Preferred Skills

• Experience with Kubernetes, container orchestration, and MLOps/LLMOps tools.
• Experience with vector databases (Pinecone, Weaviate, pgvector) or graph databases.

Key Skills

Education

Bachelor's degree