Gen AI DATA Engineer

VMC Soft Technologies, Inc; Bengaluru Urban; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

VMC Soft Technologies, Inc invites a Gen AI, Data Engineer in Bengaluru to design and build GenAI-powered data solutions. 8–12 years of IT experience preferred.

You will scale GenAI deployments (RAG/agents), productionize ML pipelines, and collaborate with data/infra teams as well as client stakeholders to deliver robust ML services on cloud platforms.

Qualifications

• Must have 6+ years of IT experience.
• Strong requirement elicitation & analysis skills.
• Ability to understand requirements & convert to design.
• Extensive knowledge on statistical and analytical analysis.
• Advanced Python, production ML.
• Generative AI (LLMs, RAG).
• Strong data engineering (SQL/ETL).
• Cloud (AWS/GCP/Azure).
• MLOps (CI/CD, Docker/K8s, MLflow).
• Model evaluation & responsible AI.

Responsibilities

• Build and scale GenAI solutions (RAG/agents).
• Productionize ML pipelines, ship Python services.
• Partner with data/infra and client stakeholders.

Skills

Generative AI (LLMs & RAG)

Model evaluation & Responsible AI

Data engineering

Productionize ML pipelines

Python

MLOps

Cloud platforms (AWS/GCP/Azure)

Docker/Kubernetes

MLflow

Tools

Docker

Kubernetes

MLflow

CI/CD tooling

Job description

Gen AI, Data Engineer

Experience Level - 8 -12 year

Location - Bangalore

Relevant skill - GeGenerative AI (LLMs, RAG) , Model evaluation & responsible AI, Data Engineering, Productionize ML pipelines

Job Requirements

• Must have 6+ years of IT experience
• Strong Requirement Elicitation & Analysis skills
• Should have the capability to understand requirements & convert to design
• Extensive knowledge on statistical and analytical analysis
• Advanced Python, production ML,
• Generative AI (LLMs, RAG),
• Strong data engineering (SQL/ETL),
• cloud (AWS/GCP/Azure),
• MLOps (CI/CD, Docker/K8s, MLflow),

Model evaluation & responsible AI.

Key Responsibilities

Build and scale GenAI solutions (RAG/agents),.

Productionize ML pipelines, ship Python services,

Partner with data/infra and client stakeholders