AI Lead Engineer

• Agent Workflow Design

  : Architect and build

  agent-based AI systems

  that include planning, memory, function-calling, and tool execution using frameworks like

  CrewAI

  ,

  AutoGen

  ,

  LangGraph

  ,

  LangChain

  , or custom orchestration.

• Solution Engineering

  : Develop modular, scalable backend services using

  FastAPI

  , integrating LLMs into microservices and pipelines.

• Multi-agent Orchestration

  : Design workflows that include

  function-calling, tool invocation, vector store retrieval,

  and conditional decision-making logic.

• CI/CD

  : Own end-to-end deployment pipelines with

  GitHub Actions

  , including test validations.

• Vector Database Integration

  : Implement

  vector-based retrieval systems

  (CromaDB, Milvus, Pinecone, Vertex AI) as part of Retrieval-Augmented Generation (RAG) strategies.

Must-Have Skills

• 5+ years

  of experience in backend engineering with

  Python

  (FastAPI, Flask) and strong architectural understanding.
• Proven track record of

  LLM-based development

  , especially with

  agentic workflows

  ,

  multi-tool agents

  , and

  decision-making logic

  .
• Experience building and deploying

  function-calling agents

  and workflows with

  LangChain

  ,

  LlamaIndex

  , or

  LangGraph

  .
• Proficiency in using

  vector databases

  like

  CromaDB

  ,

  Milvus

  ,

  Pinecone

  , or

  Vertex AI Vector Search

  .
• Excellent leadership, technical writing, and stakeholder communication skills.

Nice-to-Have Skills

• Domain knowledge in

  telecom

  ,

  cloud infrastructure automation

  , or

  enterprise AI accelerators

  .
• Familiarity with

  observability and monitoring tools

  for AI workflows (e.g., LangFuse, Arize phoenix).