Agentic AI Engineer Job in Bangalore at Siemens

Siemens is hiring for the role of Agentic AI Engineer!

Responsibilities of the Candidate:

• Designing and developing agentic AI architectures, including autonomous agents, tool-using agents, multi-agent systems, and workflow orchestration.
• Building and optimizing LLM-driven agents capable of reasoning, planning, retrieving knowledge, and executing tasks end-to-end.
• Configuring and integrating agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or internally developed frameworks.
• Developing modular tools, functions, and APIs that agents use to take actions autonomously.
• Implementing memory, context management, vector stores, and retrieval pipelines to support agent intelligence.
• Building evaluation pipelines to measure agent reliability, accuracy, and failure-mode behaviour.
• Developing scalable backend services using Python/Node that interact with agentic systems.
• Implementing CI/CD pipelines and use containerization technologies (Docker/Kubernetes) for production deployment.
• Integrating agents with enterprise systems, microservices, cloud services, and data platforms.
• Conducting POCs, model comparisons, and runtime optimizations to improve agent performance and cost efficiency.
• Working closely with product, engineering, and domain teams to build agent-powered solutions tailored to business needs.
• Staying updated with the latest advancements in LLMs, agent frameworks, reasoning engines, and cognitive architectures.
• Preparing clear documentation, architecture diagrams, and operational guidelines for agentic solutions.

Requirements:

• Strong programming skills in Python, with experience in building AI/ML applications.
• Hands-on experience with LLM integration, prompt engineering, and multi-step reasoning.
• Experience with agentic AI frameworks such as LangChain, LangGraph, AutoGen, OpenAI Assistants API, CrewAI, or equivalents.
• Solid understanding of AI/ML fundamentals, GenAI models (LLMs, embeddings), and model fine-tuning.
• Experience building and integrating REST APIs, microservices, and backend services.
• Proficiency in Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
• Experience with CI/CD pipelines (GitHub Actions, GitLab, Jenkins, etc.).
• Familiarity with vector databases (FAISS, Pinecone, Chroma, Weaviate) and RAG pipelines.
• Ability to design autonomous systems with safety, guardrails, observability, and fallback mechanisms.
• Strong debugging, problem-solving, and system-design skills.
• Ability to work collaboratively in an agile environment, handling fast-paced experimentation and iteration.