AI Engineer – LLM / RAG / Agentic AI

Role Overview

We are looking for an experienced AI Engineer with strong hands-on expertise in building and deploying LLM-powered applications, RAG systems, AI agents, document intelligence solutions, and cloud-based AI applications. This is a long-term contract opportunity for candidates who can independently design, develop, evaluate, deploy, and improve production-grade AI solutions.

Responsibilities

• Design and implement LLM agents with tool calling, function calling, dialogue state, guardrails, and safety controls.
• Build high-quality RAG and retrieval pipelines involving document indexing, chunking, embeddings, vector search, hybrid retrieval, and reranking.
• Ingest and process complex documents and PDFs using OCR and multimodal LLM-based understanding.
• Design and optimize prompts, prompt templates, and few-shot examples.
• Conduct A/B testing and automated LLM evaluations to measure grounding, hallucination, accuracy, latency, and cost.
• Deploy and monitor AI applications on cloud platforms with appropriate observability.
• Integrate AI agents with external tools and enterprise data sources.

Requirements

• 3+ years of experience building AI / ML applications.
• 1–2+ years of hands-on LLM and RAG experience.
• Strong programming expertise in Python.
• Hands-on experience with LangChain, LlamaIndex, and Hugging Face.
• Strong experience with vector databases such as Qdrant, Milvus, or Elasticsearch.
• Practical experience with chunking strategies, embedding tuning, and hybrid search.
• Experience with table extraction, document layout parsing, and OCR.
• Experience integrating tools using MCP or similar protocols.
• Hands-on cloud deployment experience with AWS, Azure, or GCP.

Nice to Have

• Experience with Generative AI and Agentic AI systems.
• Knowledge of AI agents and autonomous workflows.
• Experience implementing AI guardrails and safety mechanisms.
• Experience with LLM evaluation frameworks.
• Experience working in the Pharmaceutical / Life Sciences domain.

Skills

• Python
• LangChain
• RAG
• Vector Databases
• AWS