Agentic AI Engineer

Job Title:

Location:

Role Overview:

Join our advanced AI engineering team and play a key role in building intelligent, autonomous agents that power mission-critical workflows. You will design and operationalize enterprise-grade agentic AI systems that combine decision intelligence, retrieval automation, and LLM-driven orchestration in a highly regulated environment.

Key Responsibilities:

• Architect and develop autonomous AI agents using frameworks like LangChain, LangGraph, or similar tools.
• Build multi-agent systems supporting data retrieval, workflow automation, and complex reasoning.
• Design and implement RAG pipelines using vector databases (e.g., Pinecone, FAISS).
• Integrate and optimize LLMs for generative reasoning, memory, compliance, and guardrails.
• Develop scalable Python-based microservices/APIs for inference, chaining, and orchestration.
• Deploy solutions via Docker/Podman and cloud-native platforms.
• Implement telemetry, observability, & governance — safety checks, bias testing, model evaluation.
• Work closely with Data Science, Product, and MLOps teams to ensure scalable solution delivery.
• Ensure alignment with enterprise AI governance, security, and compliance practices.

Required Skills:

• Strong Python development experience.
• Hands-on expertise in Agentic AI frameworks (LangChain, LangGraph, AutoGen, etc.)
• Solid understanding of LLMs, embeddings, vector DBs, and memory architectures.
• Experience in RAG, prompt engineering, agent orchestration.
• Proficiency in containerization and cloud deployment.
• Familiarity with monitoring, observability, and AI governance.
• Excellent analytical, communication, and cross-functional collaboration skills.

Preferred Skills:

• Experience in healthcare or regulated domains (e.g., HIPAA, PHI compliance).
• Knowledge of AI safety, governance, and bias mitigation practices.
• Experience with LLM fine-tuning & optimization (quantization, distillation).
• Exposure to MLOps tools like MLflow, Weights & Biases.