Staff Software Engineer

Software Engineer (AI/Agentic Systems)

Key Requirements

12+ years of software engineering experience with strong expertise in designing enterprise-grade, scalable applications.

1. Advanced proficiency in Python (3.9+), including asynchronous programming, type hints, packaging, design patterns, and production-grade development practices.
2. Hands-on experience building Agentic AI systems capable of autonomous reasoning, planning, tool usage, and multi-step task execution.
3. Expertise in designing multi-agent architectures where specialized AI agents collaborate, coordinate, and delegate tasks.
4. Strong experience with LLM frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or equivalent.
5. Proven ability to develop and deploy solutions using leading Large Language Models (LLMs) including GPT, Claude, Llama, Mistral, and other foundation models.
6. Deep knowledge of Retrieval-Augmented Generation (RAG), including embeddings, chunking strategies, retrieval optimization, and knowledge-grounded AI applications.
7. Experience with AWS Bedrock, including Bedrock Agents, Bedrock Knowledge Bases, and foundation model evaluation and orchestration.
8. Expertise in AWS AgentCore for enterprise-scale AI agent deployment, lifecycle management, memory handling, and tool integration.
9. Practical experience implementing Model Context Protocol (MCP) architectures, including MCP servers, clients, and tool integrations.
10. Strong background in Vector Databases such as Pinecone, Weaviate, Chroma, Qdrant, or pgvector for semantic search and agent memory management.
11. Experience building and integrating REST APIs, event-driven services, microservices, webhooks, OAuth2, and API gateways.
12. Cloud-native development expertise on AWS, with exposure to containerization and orchestration technologies including Docker, Kubernetes, GitHub Actions, CI/CD, and MLOps pipelines.
13. Solid understanding of observability and AI monitoring, including logging, tracing, evaluation frameworks, and production governance for AI systems.
14. Strong leadership and collaboration skills, with experience working alongside product managers, data scientists, domain experts, and engineering teams while mentoring junior engineers and driving technical best practices.