Job Title: AI Engineer Generative AI & Code Intelligence Platform

Company: Siemens Healthineers

Experience: 10+ Years

Required Relevant Experience: 5+ Years in AI/ML or Generative AI

Job Function: Engineering – Software & QA / AI & Machine Learning

Employment Type: Full-time

Job Summary

We are looking for a highly experienced AI Engineer / AI Platform Architect to lead the adoption, architecture, administration and optimisation of enterprise Generative AI solutions, with a strong focus on AI coding assistants, Code LLM platforms, Agentic AI and enterprise AI platforms.

The ideal candidate will have robust hands-on experience in LLMs, Retrieval-Augmented Generation (RAG), AI platform engineering, cloud architecture, DevOps, AI governance and cost optimisation.

Key Responsibilities

- Design, deploy and manage enterprise Generative AI and LLM platforms.
- Implement and optimise RAG, GraphRAG, vector search and Agentic AI solutions.
- Evaluate and administer AI coding assistants such as GitHub Copilot, Claude Code, OpenCode or equivalent platforms.
- Develop enterprise AI architectures using Azure OpenAI, Azure AI Foundry and other cloud AI services.
- Build automated data pipelines and dashboards to track AI adoption, usage, productivity and operational KPIs.
- Implement AI FinOps practices to optimise token consumption, licensing and infrastructure costs.
- Ensure enterprise AI security, governance, compliance, scalability and reliability.
- Integrate AI platforms with GitHub, Azure DevOps, CI/CD pipelines and enterprise SDLC tools.
- Provide technical leadership, develop architecture standards and mentor engineering teams.





Mandatory Technical Skills
- Generative AI, LLMs and foundation models
- Retrieval-Augmented Generation (RAG), embeddings and vector databases
- Agentic AI and frameworks such as LangChain, LangGraph or Semantic Kernel
- Azure OpenAI, Azure AI Foundry or equivalent enterprise AI platforms
- Python, REST APIs and automation
- Cloud architecture, preferably Azure, including hybrid or multi-cloud environments
- Kubernetes, Docker, CI/CD, DevSecOps and Infrastructure as Code
- Enterprise AI platform integration, governance, security and monitoring
- Strong architecture, stakeholder management and technical leadership skills

Preferred Skills
- GitHub Copilot, Claude Code, OpenCode or equivalent AI coding assistants
- GraphRAG, Knowledge Graphs and Neo4j
- Databricks, Apache Spark, Kafka and lakehouse platforms
- Power BI or equivalent dashboarding tools
- AI FinOps, token optimisation and AI usage analytics
- Responsible AI frameworks and enterprise AI Centre of Excellence initiatives

Experience & Qualifications
- 10+ years of overall experience in enterprise IT, software engineering, platform engineering or technical architecture.
- 5+ years of hands-on experience designing, deploying and operating AI/ML or Generative AI solutions at enterprise scale.
- Proven experience delivering enterprise-grade AI solutions across complex cloud or hybrid environments.
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, AI or a related discipline.

Candidates should demonstrate hands-on implementation and architecture experience, rather than only theoretical knowledge of Generative AI.

📌 Lead AI Engineer (Bengaluru)
🏢 Sunovaa Tech
📍 Bengaluru