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

  • Set architecture direction for full-stack and AI platforms across multiple initiatives
  • Build reusable AI components for forward-deployed engineers, along with resilient REST APIs and microservices
  • Develop RAG and multimodal LLM capabilities, plus agent workflows that handle tasks autonomously
  • Make end-to-end technical choices that balance AI system reliability, speed and cloud costs
  • Mentor engineers and guide contractors and partners on delivery

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 bachelor's degree in computer science, computer engineering or a related technical discipline
  • A record of shipping production applications that use LLMs or AI services at scale
  • Experience leading technical teams, guiding external contractors or vendors, and driving at least five AI/ML-engaged projects
  • Hands-on cloud and containerization experience, including AWS or Azure and Docker or Kubernetes

Who this fits

This senior staff role suits an engineer who can set technical direction, build AI-enabled services and mentor others. It is based in Bengaluru, India, with a hybrid arrangement; relocation assistance is provided. You'll work with globally distributed teams.

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