Description

You embed with client teams to understand manual business workflows and build AI-agent-powered automation to replace them. You own the solution end-to-end—discovery, build, deploy, iterate—working directly with clients with minimal direction.

This role is on-site.

Responsibilities

• Design and build reusable skills consumable by LLM-powered agent workflows.
• Build and consume MCP servers to expose and integrate tools for agent use.
• Implement multi-agent coordination, task delegation, and result aggregation across agent networks.
• Develop RAG pipelines using vector databases, chunking, and embeddings.
• Decompose manual business processes into agent pipelines and integrate with enterprise systems like SharePoint, Jira, and SAP.

Required Skills

• Python 3.10+ with async/await, type hints, and FastAPI.
• Agentic AI frameworks: Strands (primary); awareness of LangGraph, CrewAI, or AutoGen.
• LLM API fundamentals: tool use, function calling, streaming, and context management.
• Backend infrastructure: AWS (EC2/ECS, Lambda, RDS, S3), Docker, and GitHub Actions CI/CD.
• Database knowledge: Basic SQL (query, filter, join) and vector DBs (pgvector, Pinecone, OpenSearch).
• Security and authentication: REST API design, JWT, and OAuth2.
• Proven experience in software engineering with at least one production project involving LLM agents, skill building, or RAG pipelines.

Preferred Skills

• Next.js 15+, TypeScript, and Tailwind CSS.
• Terraform, Kubernetes, or RPA tools (UiPath, Power Automate).

Key Skills

Education

Any Gradute