Senior AI Solution Engineer _ GSO

Siemens Mobility; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Siemens Mobility in Bengaluru is seeking a Senior AI Solution engineer to drive AI adoption across service operation units. You will identify, prototype and implement practical AI delivering measurable business value.

You will develop Generative AI solutions including RAG pipelines and multi-agent systems, collaborating with architects, data engineers, and domain experts to produce scalable, enterprise-grade systems and ensure responsible AI practices.

Qualifications

• Bachelor’s or master’s degree in computer science, data science, engineering, or equivalent experience.
• 4+ years owning domain strategy, governance, delivery and stakeholder engagement.
• 4–6 years delivering AI/ML, data science solutions in production.
• 2–3 years focused on Generative AI/LLM applications.

Responsibilities

• Identify and assess AI, GenAI, Agentic AI, and automation opportunities across service operation units.
• Translate challenges into AI-enabled use cases focused on automation and productivity.
• Rapidly design and develop proof-of-concepts using Azure AI Foundry, Copilot, Power Platform, Mendix.
• Support deployment, monitoring, and continuous improvement of AI solutions.
• Provide technical leadership on AI governance, responsible AI, and adoption of best practices.
• Track emerging technologies and recommend innovations that create business value.

Skills

GenAI/LLM

AI architecture

Python

Docker/Kubernetes

Azure/AWS

LangGraph/Semantic Kernel

Stakeholder mgmt

Cross-functional teams

Education

Bachelor's/Master's in CS or equivalent

Tools

LangGraph

Semantic Kernel

Azure OpenAI

Azure AI Search

Pinecone

Job description

We’re seeking a Senior AI Solution engineer to drive AI adoption across one of the service operation business units. Major responsibility will be to identify, prototype and implement practical AI that delivers measurable business value.

Senior AI solution engineer will be responsible for producing Generative AI solutions, including RAG pipelines and multi-agent systems—to automate workflows and drive operational excellence. You’ll work closely with solution/data architects, software developers, data engineers, and domain experts to rapidly prototype and deliver scalable, enterprise-grade systems.

This is an individual contributor role requiring strong research skills, deep expertise in AI foundation models, and the ability to translate cutting-edge concepts into impactful solutions for service operation challenges.

A Snapshot of your Day

How You’ll Make an Impact (responsibilities of role)

Strategic

• Identify and assess AI, GenAI, Agentic AI, and automation opportunities across service operation business units.
• Conduct business workshops and convert operational challenges into AI-enabled use cases focused on automation and productivity enhancement opportunities.
• Rapidly design and develop proof-of-concepts using Azure AI Foundry, Microsoft Copilot, Power Platform, and Mendix.
• Support deployment, monitoring, and continuous improvement of AI solutions.
• Provide technical leadership on AI governance, responsible AI, and adoption of best practices.
• Track emerging technologies and recommend innovations that create business value.

Operational

• Design and implement RAG pipelines, agentic workflows, and LLM integrations for tasks such as document understanding, classification, and knowledge assistance.
• Build agent-based applications for planning, tool use, and execution using frameworks like LangGraph, Semantic Kernel, and prompt orchestration tools.
• Architect data pipelines and cloud solutions for training, deployment, and monitoring on Azure/AWS with Docker, Kubernetes, and CI/CD.
• Convert problem statements into prototypes, iterate with stakeholders, and harden into production-ready microservices (FastAPI) with APIs and event-driven workflows.
• Define rigorous evaluation metrics for LLM/ML systems (accuracy, latency, cost, safety), optimize retrieval quality, prompt strategies, and agent policies.
• Implement Responsible AI guardrails, data privacy, PII handling, access controls, and auditability.

What You Bring (required qualification and skill sets)

• Bachelor’s/master’s in computer science, Data Science, Engineering, or equivalent experience
• This role requires 4+ years of experience and ownership of domain-specific strategy, overnance, delivery and stakeholder engagement.
• 4–6 years delivering AI/ML, Data Science solutions in production.
• 2-3 years focused on Generative AI/LLM applications.
• Strong communication and stakeholder management skills
• Experience working in global cross-functional teams
• Strong Experience in AI architecture (scalable, modern, and secure) design across AI/ML enterprise solutions.

Technical Skills:

oGenAI Expertise:

• Embeddings and vector databases (FAISS, Azure AI Search, Pinecone).
• Agent frameworks (LangGraph, Semantic Kernel) and orchestration strategies.
• Model selection/fine-tuning, cost-performance optimization, safety filters.

oCloud & Data: Hands-on with Azure/AWS; experience with Azure OpenAI, Azure AI Search, Microsoft Fabric/Databricks (preferred), Snowflake or similar DWH.

oArchitecture: Microservices, event-driven design, API security, scalability, and resilience.

Preferred Qualifications

• Experience with Azure OpenAI, Microsoft Fabric/Prompt Flow, Copilot Studio connectors, or enterprise integrations (SharePoint/Teams).
• Expertise in ML/DL techniques: time-series forecasting, anomaly detection, NLP document AI (OCR, classification, extraction).
• Familiarity with security (OAuth2, RBAC), observability (OpenTelemetry), and cost governance (token budgeting).
• Languages/Frameworks: Python, FastAPI/Flask, LangGraph/Semantic Kernel/CrewAI/AutoGen, scikit-learn, PyTorch/TensorFlow.
• Ops: Docker, Kubernetes, GitHub Actions/Jenkins, Helm, monitoring/logging.