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Lead Gen AI Engineer

Lead Gen AI Engineer

ImpetusKottayam, IN
15 hours ago
Job description

About the Role :

We are looking for a Software Engineer who combines deep data engineering expertise with hands-on experience in Generative AI and Agentic AI system development on AWS Cloud.

This role is ideal for someone who can design, build, and deploy production-grade GenAI workflows integrating LLMs, vector databases, and orchestration frameworks—with the same rigor as a traditional data system.

Key Responsibilities :

  • Design and maintain data pipelines and AI data infrastructure on AWS (Glue, Lambda, S3, Redshift, Step Functions, Athena, etc.).
  • Develop and deploy LLM-based applications and Agentic AI workflows using frameworks like LangChain, LlamaIndex, or AutoGen.
  • Build RAG (Retrieval-Augmented Generation) pipelines using AWS services (S3 + Bedrock + SageMaker + OpenSearch / Vector DB).
  • Implement agentic reasoning, tool calling, and orchestration for multi-agent workflows.
  • Containerize and deploy AI services using Docker, ECS, or EKS, ensuring scalability, cost-efficiency, and observability.
  • Integrate AWS Bedrock, SageMaker, or OpenAI APIs with internal data systems and applications.
  • Set up monitoring, tracing, and model observability using AWS CloudWatch, X-Ray, or third-party LLMOps tools.
  • Collaborate with ML engineers, data scientists, and architects to take GenAI prototypes to production-ready deployments.

Required Skills & Experience :

  • 6–10 years of total experience in Data Engineering with strong AWS background.
  • Proficiency in Pyspark with hands-on production grade experience.
  • Hands-on experience with GenAI solutions in real-world environments (not just demos or PoCs).
  • Working knowledge of Agentic AI frameworks (LangChain, LlamaIndex, AutoGen, or similar).
  • Good hands-on experience in Python
  • Cloud experience is must have, AWS is preferred.
  • Experience with RAG architecture, vector databases (OpenSearch, Pinecone, FAISS, Chroma, or Milvus), and embedding models.
  • Understanding of LLMOps, prompt lifecycle management, and performance monitoring.
  • Practical experience deploying workloads on AWS ECS / EKS, setting up CI / CD pipelines, and managing runtime performance.
  • Familiarity with IAM, VPC, Secrets Manager, and security best practices in cloud environments.

    • Nice to Have :

  • Experience with AWS Bedrock for model hosting or SageMaker for fine-tuning and evaluation.
  • Exposure to multi-agent architectures and autonomous task orchestration.
  • Contributions to open-source GenAI projects or internal AI platform initiatives.

    • For Quick Response- Interested Candidates can directly share their resume along with the details like Notice Period, Current CTC and Expected CTC at anubhav.pathania@impetus.com

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