AI Native Solutions Lead (Agentic / Applied)

About the role

You will design, build, and deploy production‑grade agentic AI systems across the enterprise technology stack, working directly with client development teams and leading technical design sessions.

Key responsibilities

• Architect and govern multi‑agent orchestration, RAG pipelines, policy routing, memory management, and lifecycle observability at enterprise scale.
• Define standards for RAG pipelines, multi‑LLM integration, and LLM Ops, including cost governance and safety monitoring.
• Lead senior‑level client engagements, facilitate architecture design sessions, and deliver proof‑of‑concept solutions.
• Publish reusable patterns, accelerators, and development standards to accelerate future engagements.
• Own measurement frameworks for system quality, defining accuracy, latency, safety, and cost metrics.

Required profile

• Bachelor’s degree or college diploma in a related field.
• 10+ years of software development experience in production environments.
• At least 1 year designing and deploying agentic AI solutions in production.
• Proven experience leading software development teams and client‑facing technical engagements.

Required skills

• Python (primary language) and Java or equivalent backend language.
• Agentic orchestration frameworks such as LangGraph, CrewAI, AutoGen.
• LLM API integration (OpenAI, Anthropic, Vertex AI) with provider abstraction and token management.
• RAG pipeline development: embeddings, chunking, vector databases, context design.
• LLM Ops practices: eval harness design, prompt versioning, production observability.
• Cloud‑native development: Kubernetes, Docker, microservices, serverless, CI/CD, Terraform or Helm.