aimlroles

Staff Software Engineer- AI/ML

Gevernova gevernova.com Open · verified Oct 22, 2026
Hybrid Bengaluru Full-time Senior AI Engineering

At a glance

Senior AI Engineering role at Gevernova. Bengaluru · full-time.

Pay not stated AI Engineering salary

RoleAI Engineering
SenioritySenior
LocationBengaluru
WorkplaceHybrid
EmploymentFull-time
PostedOct 7, 2026 · 2w ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Shape the architecture for enterprise software and AI platforms across several initiatives
  • Build reusable AI components, resilient REST APIs, and microservices for forward-deployed engineers
  • Deliver retrieval-based and multimodal language-model features, plus agent workflows for autonomous tasks
  • Set practices for AI-assisted development and make end-to-end technical calls on reliability, speed, and cloud cost
  • Coach engineers and guide contractors and partners on technical work

What you bring

  • At least ten years using a general-purpose language such as Python, Java, or Go, plus JavaScript or TypeScript front-end work
  • A computer science, computer engineering, or related technical degree
  • A record of delivering production applications using LLMs or AI services at scale, and leading at least five AI/ML-heavy projects
  • Experience leading technical teams, guiding external vendors or contractors, and working across globally distributed teams
  • Strong cloud and container skills, including AWS or Azure and Docker or Kubernetes

Who this fits

This staff-level role suits a hands-on technical leader who can guide teams while shaping and shipping AI systems. The position is hybrid in Bengaluru, India, and relocation assistance is available.

From the employer

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