Staff Software Engineer, AI Solutions & Platforms
Staff Engineer leading architecture, design, and hands-on development of enterprise AI/GenAI solutions—LLMs, RAG, and agentic workflows—using Python, FastAPI, LangChain/LangGraph, and Azure OpenAI at a global life-sciences company.
- Compensation
- Not disclosed
- Location
- Bangalore, India
- Work setup
- Not specified
- Seniority
- Staff
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Bachelor's degree in computer science, engineering, or related technical field
- 10+ years of industry experience in software engineering and AI solutions
- Multiple years specializing in production-grade AI/ML solutions
- 5+ years in agile/scrum environments
- 5+ years building scalable backend systems with Python and REST APIs (FastAPI preferred)
- Proficiency with Git-based workflows, CI/CD pipelines, and automated testing
- Proficiency with containerization and orchestration (Docker, Kubernetes)
- Practical experience integrating and operating LLMs using Azure OpenAI, Anthropic Claude, or OpenAI-compatible APIs
- Experience with Ollama or similar for local and on-premises inference and evaluation
- Hands-on experience with RAG and agentic AI (embeddings, vector search, tool calling, prompt engineering, evaluation)
- Experience with LangChain and LangGraph for LLM orchestration and agentic workflows
- Experience with data stores and vector indexes (PostgreSQL/pgvector, Qdrant)
- Strong data engineering skills including ETL, large-scale data processing (Pandas, NumPy)
- Excellent written and verbal communication skills
Nice to have
- Master's degree
- Experience with MLOps tools (MLflow, Kubeflow)
- Experience with ML frameworks (scikit-learn, PyTorch)
- Experience with model evaluation frameworks and model governance
- Experience with cloud platforms (Azure, AWS, GCP)
Full description
Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
- About the Role
At Thermo Fisher Scientific, you’ll do meaningful work that makes a positive global impact. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner, and safer. With industry-leading R&D investment, we empower our teams to solve complex scientific challenges—from environmental protection to advancing healthcare and cancer research.
As a Staff Engineer, AI Solutions & Platforms, you will provide end-to-end architectural, design, and technical leadership across multiple teams delivering enterprise-grade AI and Generative AI solutions. As a hands-on technical leader and architect, you will own system design decisions, define reference architectures, and guide implementation of AI-powered capabilities, including deep learning models, LLMs, RAG solutions and agentic workflows across internal and external customer-facing applications. You’ll also mentor engineers, influence platform strategy, and ensure AI-driven systems are secure, resilient and production-ready. A successful candidate in this role is expected to collaborate effectively with the broader teams, and consistently deliver well-architected, scalable, secure, production-grade AI and Generative AI features supporting a variety of use cases and scientific products, with measurable impact on scientific workflows, customer outcomes and innovation velocity.
Key Responsibilities
- Provide software and systems architecture leadership including reference architectures, design standards, patterns, and best practices for AI and Generative AI platforms and solutions.
- Own high-level and low-level system design, including component architecture, data flows, integration patterns, and deployment strategies.
- Design and evolve cloud-native, event-driven, and API-first architectures for AI-enabled products and platforms.
- Design, develop, and integrate Generative AI systems using LangChain and LangGraph for agentic workflows and orchestration.
- Architect and implement agentic AI and RAG workflows, including data ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, and prompt engineering.
- Build and deploy LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
- Leverage Ollama for local and on-prem LLM system experimentation and evaluation.
- Integrate AI/Generative AI capabilities across enterprise platforms, and scientific applications and workflows.
- Actively contribute to hands-on development using Python and modern backend frameworks such as FastAPI.
- Design and build well-structured, maintainable, and extensible APIs supporting AI and data-driven workloads.