Senior Software Engineer - AI/ML ( Platform )

Cognite · Bengaluru

  • Experience6–10 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Posted23 Sept 2026
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About Cognite

Cognite is hiring in Bengaluru in technology software. This role looks for around 6+ years of experience.

Skills

  • Python
  • Docker
  • Kubernetes
  • REST APIs
  • gRPC APIs
  • asynchronous programming
  • containerization
  • vector databases
  • LLM agents
  • model serving
  • AI pipelines
  • prompt tracking
  • system architecture
  • high-concurrency applications

The role

A generative AI engineer at an industrial software company builds production services for industrial data problems, architecting vector databases and LLM agents while developing Python APIs. The role also applies Docker to reliable AI pipelines and asynchronous applications.

Full job description

About the Role:

We are looking for a Senior Software Engineer to lead the production systems for our Context Services team. You will serve as the bridge between our Applied Scientists/AI Engineers and the central Platform Engineering team. In this role, you will focus on turning complex analytical solutions—ranging from traditional ML/DL models to modern LLM agents—into highly reliable, production-grade software services.

The Impact you bring to CogniteKey Responsibilities:Architecture & Scale: Design robust system architectures and develop low-latency APIs/services capable of supporting thousands of concurrent users with sub-second response times.Cross-Functional Problem Solving: Collaborate closely with product, architecture, and AI teams to translate complex industrial data problems into scalable solutions.AI & LLM Orchestration: Architect frameworks for model serving, vector databases, and agentic workflows (LLM agents), ensuring reliable state management and prompt tracking.Platform Integration: Act as the technical liaison with the central Platform team, leveraging core infrastructure to build reliable AI pipelines and workflows.Innovation: Drive technical innovation through research, prototyping, and potential contributions to open-source initiatives.

Qualifications & Skills:Experience: 6–10 years of industry experience in Software Engineering, Backend Engineering, or Systems Engineering, with exposure to AI, ML, or LLM-based production systems.Programming: Strong proficiency in Python and experience building high-concurrency applications, asynchronous programming, or REST/gRPC APIs.Systems: Solid understanding of containerization (Docker) and modern deployment environments (such as Kubernetes or cloud platforms).AI Knowledge: Familiarity with the broader AI lifecycle—including traditional model registries, vector databases, or LLM evaluation frameworks—is a major plus, but a strong ability to learn new paradigms is essential.