Gen AI Lead/ Architect

Hiring!!!!

We are looking for an Immediate joiner to 15 days Notice period. Please get back if you can negotiate your notice period. 

GenAI Engineer - Development

Experience : 8-10 yrs (Lead)

Must be comfortable partnering with Nike engineers and our governance processes.

Required Skills:

• Agentic Development/ Observability: Hands on experience with tools such as LangSmith/ Langfuse/Data Dog. Building Multi-agent services. Exposure to monitoring and tracing multi-agent/LLM workflows concepts, tool-call tracing, latency/cost/drift monitoring, Smart LLM routing, Cost Optimization and Multi-Cloud Decisioning (AWS/GCP, etc)

• Agentic Governance: guardrails and safety controls for autonomous agents, human-in-the-loop design, audit logging, and responsible AI/compliance frameworks.

• Data Strategy: experience contributing to or advising on enterprise data strategy, data architecture roadmaps, and data-driven decision-making frameworks.

• Dev Data Platforms: data pipeline design, and data engineering fundamentals is mandatory. Hands-on experience with modern data platform tooling (e.g., Databricks, Snowflake, or similar lakehouse/warehouse platforms) is a plus.

• DevOps: Exposure to CI/CD pipeline design (e.g., Jenkins, GitHub Actions, Azure DevOps), infrastructure as code (Terraform or equivalent), and automated testing/release practices.

Core GenAI Engineering Skills:

• Strong programming skills in Python (or similar) for building GenAI applications.

• Experience with LLM application frameworks such as LangChain, LangGraph, Semantic Kernel, or AutoGen.

• Experience with RAG architectures, vector databases (e.g., Pinecone, Weaviate, FAISS, pgvector), and embeddings.

• Familiarity with prompt engineering, fine-tuning/instruction-tuning, and evaluation of LLM outputs.

• Experience integrating with major LLM providers/platforms such as OpenAI, Anthropic, Azure OpenAI, or AWS Bedrock.

• Understanding of MLOps/LLMOps practices for model deployment and lifecycle management.