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Staff AI Software Engineer at GE Vernova — Bengaluru

Experience6+ yrs
SalaryNot disclosed
Work modeunknown
Levelstaff
Posted11 Sept 2026

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About GE Vernova

GE Vernova is hiring in Bengaluru in energy utilities. This role looks for around 6+ years of experience.

The role

Staff AI Software Engineer role at GE Vernova focused on building and deploying an AI platform with AI agents and MCP (Model Context Protocol) servers, end-to-end feature delivery, and production support. You will implement LLM/generative AI capabilities including structured prompting, memory management, context management, and RAG patterns (embeddings + retrieval), with testing for prompts and model performance plus observability. Required skills include Python (preferred) plus Java or Go, JavaScript/TypeScript, AWS/GCP/Azure, Docker and Kubernetes, and working with LLMs/MCPs/AIO services; preferred tools include Amazon Bedrock AgentCore and LangChain, React/Vue/Angular, vector databases like pgvector, and AI orchestration frameworks; experience level is 6+ years (10+ preferred). Based in Bengaluru, Karnataka, India (work mode not specified).

Full job description

Job Description Summary

As a Staff AI Engineer, you will lead the architecture, development, and end-to-end lifecycle of our AI platform and the underlying infrastructure that powers it. You will design and deploy AI agents and robust MCP (Model Context Protocol) servers that standardize data connectivity, skills, and tools. You will also own the full stack, from architectural design and clean code implementation to rigorous testing and production support. By balancing high-level system strategy with hands-on technical execution, you will ensure our agentic workflows are scalable, secure, and seamlessly integrated into the enterprise ecosystem.

You will partner with internal teams and external contractors to lead technical reviews, integrations, and delivery execution. You will drive Agile practices, establish testing approaches for prompts and model performance, and implement observability for AI features. We value autonomy, continuous learning, and clear business impact. If you are excited by this work but unsure whether you meet every requirement, we encourage you to apply.

Responsibilities

Job Description

Collaborate with cross-functional teams (product, design, operations, infrastructure) to build AI-native application experiencesBuild AI Agents, MCP Servers, Tools and integrate LLM / generative AI capabilities into products, including structured prompting, memory management and context management.Implement retrieval-augmented generation (RAG) patterns (e.g., embeddings + retrieval) and contribute to context-aware and personalized user experiencesDrive end-to-end execution of medium-to-large features with independence, contribute to technical direction within the teamMentor engineers; guide contractors and partners.

Required Qualifications

Bachelor’s degree in computer science, Computer Engineering, or related technical field6+ years of experience using at least one general purpose programming language (Python [preferred], Java, or Go) and front-end experience with JavaScript/TypeScriptProven track record shipping production applications that incorporate LLMs, MCPs or AI services at scaleDemonstrated experience leading technical teams and providing guidance to external contractors or vendorsStrong experience with cloud platforms (AWS, GCP, or Azure) and advanced containerization (Docker, Kubernetes)Experience with technical oversight, code review processes, and quality assurance methodologies

Preferred Qualifications

10+ years of experience in Cloud Software Development, including architecture design, technical leadership, and system optimizationExperience with Strands, ADK or Agent development frameworks.Experience with multiple LLM providers and advanced AI orchestration frameworks (e.g. Amazon Bedrock AgentCore, LangChain)Experience with modern front-end frameworks (React, Vue, or Angular) and advanced state managementExperience with vector databases (e.g. pgvector) and embedding model optimizationExperience with enterprise RAG architectures, semantic search optimization, and conversation memory management at scaleExperience building and scaling AI-powered features for 100k+ users

Additional Information

Relocation Assistance Provided: Yes