Staff Software Engineer - AI/ML

GE Vernova; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Benefits offered by this job

Relocation assistance provided

Job summary

GE Vernova in Bengaluru seeks a Staff AI Engineer to lead enterprise full stack and AI platform architecture. You will design and ship microservices and REST APIs, build RAG and multimodal LLM features, and set standards for AI-assisted development.

You will partner with globally distributed teams to accelerate assimilation of AI into Grid SW services, delivering tangible outcomes while balancing performance, reliability and cloud costs.

Qualifications

• Bachelor’s degree in computer science, computer engineering, or related field.
• 10+ years of experience with Python, Java, or Go and front-end JS/TS.
• Proven track record shipping production apps with LLMs or AI services at scale.
• Experience leading technical teams and guiding external contractors or vendors.
• Led at least 5 AI/ML projects with strong AI engagement.
• Strong cloud experience (AWS or Azure) and advanced Docker/Kubernetes capabilities.
• Experience with code reviews and QA methodologies.
• Excellent communication and ability to collaborate with globally distributed teams.

Responsibilities

• Identify and deliver reusable AI components for forward-deployed engineers.
• Ship resilient REST APIs and microservices.
• Build RAG and multimodal LLM features.
• Design agentic workflows for autonomous tasks.
• Mentor engineers and provide guidance to contractors and partners.

Skills

Python

Java

Go

JavaScript/TypeScript

LLMs/AI services

Cloud: AWS

Cloud: Azure

Docker

Kubernetes

Leadership

Mentoring

Distributed teams

Education

Bachelor's degree in CS/CE or related field

Tools

MuleSoft

SOAP/REST

Milvus

Pinecone

Weaviate

LangChain

LlamaIndex

Job description

Job Description Summary

Job Description Summary

As a Staff AI Engineer, you’ll lead enterprise full stack and AI platform architecture at scale for multiple initiatives across the company. You’ll design and ship microservices and REST APIs, build RAG and multimodal LLM features, and set standards for AI-assisted development. You’ll make technical decisions end-to-end, balancing reliability, performance, and cloud cost for AI systems.

You will partner with globally distributed teams to engage, intervene and accelerate assimilation of AI into Grid SW services activities that drive tangible outcomes.

Job Description

Key Responsibilities

• Identify and deliver reusable AI components for forward-deployed engineers.
• Ship resilient REST APIs and microservices.
• Build RAG and multimodal LLM features.
• Design agentic workflows for autonomous tasks.
• Mentor engineers and provide guidance to contractors and partners.

Required Qualifications

• Bachelor’s degree in computer science, Computer Engineering, or a related technical field.
• 10+ years of experience with at least one general purpose programming language (Python [preferred], Java, or Go) and front-end experience with JavaScript/TypeScript.
• Proven track record shipping production applications that incorporate LLMs or AI services at scale.
• Demonstrated experience leading technical teams and providing guidance to external contractors or vendors.
• Demonstrated experience of driving at least 5 projects with strong AI & ML engagement
• Strong experience with cloud platforms (AWS or Azure) and advanced containerization (Docker, Kubernetes).
• Experience with technical oversight, code review processes, and quality assurance methodologies.
• Strong trouble shooting skills
• Good communication skills and prior experience of working with globally distributed teams

Preferred Qualifications

• Experience in AI/ML, including architectural design, technical leadership, and system optimization.
• Having a master's degree or equivalent in AI is a plus.
• Experience with modern integration frameworks (SOAP, Rest, MuleSoft, ) and advanced state management.
• Experience with vector databases (e.g. Milvus, Pinecone, Weaviate, pgvector) and embedding model optimization.
• Experience with multiple LLM providers and advanced AI-orchestration frameworks (e.g. LangChain, LlamaIndex).
• Experience with enterprise RAG architectures, semantic search optimization, and conversation memory management at scale.
• Experience building and scaling AI-powered features for 100k+ users.

Additional Information

Relocation Assistance Provided: Yes