AI/ML Engineer (Agentic AI Focus) For Gurgaon Location ; immediate

Dear Candidate,

urgent requirement for a Data Science / AI-ML Engineer (Agentic AI Focus)

updated profile

Job Details

• Job Location:

  Gurgaon

• Experience:

  4+ Years

• Role:

  Data Science / AI-ML Engineer (Agentic AI Focus)

• Skills:

  Data Science, AI/ML, Agentic AI

• Interview Process:

• Round 1: Technical Virtual
• Round 2: Technical Virtual / Face-to-Face
• Round 3: HR

Role Overview

AI/ML Engineer

multi-modal AI agents

Key Responsibilities

Agentic AI & LLM Development

• Design and build autonomous

  Agentic AI systems

  using

  Google Cloud Vertex AI

  and LLMs (Gemini, OpenAI, etc.).
• Implement

  multi-modal AI solutions

  handling text, voice, and structured data.
• Develop AI agents for

  voice interactions and servicing automation

  with natural, context-aware responses.

Cloud AI & Workflow Automation

• Utilize

  Google Cloud Platform (GCP)

  services including

  Vertex AI

  and

  BigQuery

  .
• Orchestrate end-to-end workflows using

  n8n

  and

  Zapier

  , integrating APIs and enterprise systems.
• Build and optimize

  Retrieval-Augmented Generation (RAG)

  pipelines for enterprise and financial data.

Model Deployment & Optimization

• Deploy AI/ML models into production ensuring

  low latency, scalability, and high availability

  .
• Continuously monitor and improve agent performance and conversation accuracy.
• Develop ML models for

  financial services use cases

  such as fraud detection, risk assessment, and personalized recommendations.

Must-Have Skills & Experience

• Experience:

  47 years in AI/ML Engineering with 2+ years in

  Generative AI & LLMs

  .
• Proven experience deploying

  Agentic AI or autonomous systems

  in production.

• Programming:

  Strong proficiency in

  Python

  .

• Agentic AI & LLMs:

  LangChain, AutoGen, Vertex AI Agents, prompt engineering.

• Cloud AI Stack:

  Vertex AI (Agent Builder, Model Garden), BigQuery.

• Automation Tools:

  n8n, Zapier.

• Voice AI:

  STT/TTS and conversational AI platforms.

• Domain Expertise:

  Financial Services AI experience is mandatory.

Good-to-Have Skills

• Database, API integrations, and ETL pipelines.
• DevOps for AI: CI/CD, Docker, Kubernetes.

• Certification:

  GCP Professional Machine Learning Engineer.

Education

• B.Tech / B.E / MCA / M.Sc

  or equivalent inComputer Science, Artificial Intelligence, or Data Science.

Thanks & Regards,