Senior AI/ML Engineer – Agentic AI

About the Role

highly skilled and innovative AI/ML Engineer (Contract role)

Agentic AI frameworks

Key Responsibilities

• Design, build, and deploy

  Multimodal RAG architectures

  and

  LangGraph-based Agentic AI systems

  for enterprise automation.
• Develop and optimize

  chunking strategies, embedding pipelines

  , and

  vector database integrations

  (Vertex AI, PGVector, Pinecone).
• Integrate

  LLMs (Gemini 2.5, Gemma, LLaMA 4, etc.)

  into GenAI workflows and automation pipelines.
• Implement and maintain

  CI/CD pipelines

  , supporting

  MLOps/LLMOps

  frameworks for continuous delivery.
• Collaborate with cross-functional teams to ensure

  scalable deployment

  on

  GCP (Vertex AI)

  platforms.
• Continuously evaluate, monitor, and fine-tune models for

  precision, recall, relevance, faithfulness

  , and

  cost efficiency

  .
• Contribute to the development of

  evaluation frameworks (e.g., RAGAS)

  and

  AI efficacy dashboards.

Required Skills & Experience

• Minimum

  4+ years of experience

  in

  AI/ML model development

  with a focus on

  GenAI, RAG, or Agentic AI

  systems.
• Proven hands-on experience with:

• Vector databases:

  PGVector, Pinecone, or similar

• Multimodal data processing:

  text, image, audio embeddings and chunking

• Embedding models

  and

  vector search optimization

• Practical knowledge of

  LangChain, LangGraph

  , and

  LLMOps

  toolkits.
• Familiarity with

  GCP Vertex AI

  or equivalent ML platforms.
• Experience with

  CI/CD

  ,

  MLflow

  , or other MLOps automation pipelines.
• Exposure to

  prompt engineering, fine-tuning

  , and

  LLM model integration

  .

Good to Have

• Bachelor’s or Master’s degree in

  Computer Science, AI/ML, Data Science

  , or related disciplines.

• GCP/AWS/ML certifications

  are an advantage.
• Contributions to

  open-source AI projects

  or publications in

  GenAI / RAG / Agentic AI

  domains.
• Strong problem-solving ability and a mindset for

  rapid prototyping and experimentation

  .