Agentic AI Engineer

1 day ago

Hyderabad, Telangana, India 518c6aa2-d08a-45a7-97db-d037b1c62852 Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Job Title:
Agentic AI Engineer

Location:
Hyderabad (Onsite)

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.

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