Description

You will build and maintain agentic AI solutions, focusing on LLM orchestration, retrieval-augmented generation (RAG), and production readiness. Your work ensures safe, observable, and compliant AI systems in regulated environments.

Responsibilities

• Develop LLM/agent orchestration patterns including planner/supervisor architectures, tool-using agents, and routing logic.
• Implement intent classification, information extraction, and decision logic for servicing workflows with downstream integrations.
• Design RAG pipelines for policy grounding, managing knowledge ingestion, chunking strategies, embeddings, and re-ranking.
• Define evaluation frameworks using golden datasets and automated scoring to reduce hallucinations and ensure safety.
• Implement observability for agent latency, cost, and drift while supporting CI/CD for prompt versioning and rollbacks.

Required Skills

• 5+ years of software engineering experience with strong CS fundamentals.
• Hands-on experience building with LLMs, agents, RAG, and tool/function calling.
• Strong proficiency in Python and building backend services/APIs.
• Experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
• Experience with vector databases and search (Pinecone, Weaviate, Milvus, OpenSearch/Elastic).
• Experience deploying services in cloud environments (AWS, Azure, GCP) with DevOps practices.
• Strong understanding of security and privacy principles (PII handling, least privilege, audit logging).

Preferred Skills

• Experience in financial services or regulated domains (risk controls, compliance audit readiness).
• Familiarity with enterprise workflow integrations (ServiceNow, RPA, BPM) and messaging systems (Kafka/SQS).

Key Skills

Education

Any Gradute