Sr. Staff AI Architect
Thermo Fisher Scientific17 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Provide enterprise-wide architectural and technical leadership for Generative AI and agentic AI platforms across multiple engineering teams.
- Define the architecture, roadmap, standards, and reusable components for an enterprise agentic harness and runtime platform.
- Design distributed, cloud-native, event-driven, API-first systems covering agent planning, orchestration, memory, tool execution, state management, human approvals, and failure recovery.
- Design and implement agentic systems using LangGraph, LangChain, Python, FastAPI, LLM integrations, and RAG architectures.
- Define model routing, provider abstraction, fallback, latency optimization, token management, cost controls, and safe autonomous execution patterns.
- Establish evaluation, regression testing, observability, debugging, replay, monitoring, governance, disaster recovery, and data protection practices for AI systems.
- Build reference implementations and backend platform components, including APIs, service boundaries, data models, workflow interfaces, and event schemas.
- Guide the use of PostgreSQL, pgvector, Qdrant, event streaming, caching, and persistent workflow storage.
- Lead architecture and design reviews, technical investigations, architecture decision records, and cross-team technical strategy.
- Mentor architects, staff engineers, senior engineers, and technical leads while leading communities of practice and communicating with technical and non-technical stakeholders.
Requirements
- Bachelor’s degree in Engineering or master’s degree in Computer Science with 15+ years of proven industry experience, including software architecture, platform engineering, and technical leadership.
- 8+ years of experience building scalable backend systems and APIs using Python and FastAPI.
- Proven experience defining enterprise architecture and technical strategy across multiple products or engineering teams.
- Strong knowledge of distributed systems, microservices, event-driven architecture, asynchronous processing, messaging, caching, and workflow orchestration.
- Experience with cloud-native architecture on Azure, AWS, or GCP and proficiency with Git, automated delivery pipelines, infrastructure automation, and release management.
- Experience with pytest, unittest, integration testing, contract testing, and automated quality strategies.
- Deep hands-on experience designing and implementing agentic AI systems, agentic harnesses, orchestration, tool and function calling, multi-agent coordination, memory, state management, guardrails, recovery, tracing, and replay.
- Experience integrating Azure OpenAI, Anthropic Claude, OpenAI-compatible APIs, and local inference platforms such as Ollama.
- Experience with prompt engineering, structured outputs, context management, output validation, RAG, embeddings, semantic and hybrid search, reranking, grounding, and citation patterns.
- Hands-on experience with PostgreSQL, pgvector, and Qdrant, along with data ingestion, ETL, preprocessing, metadata management, large-scale data processing, knowledge graphs, and domain ontologies.
- Experience evaluating nondeterministic AI and agentic systems using golden datasets, regression testing, quality metrics, observability, LLMOps, model gateways, monitoring, and deployment governance.
- Understanding of AI security, privacy, access control, responsible AI, auditability, and governance.
- 5+ years of experience working in Agile/Scrum or comparable product development environments, plus demonstrated mentoring and strong written and verbal communication.
- Preferred experience includes Azure services such as AKS, managed identity, Azure AI services, eventing, security, and monitoring; MCP; durable workflow engines; MLflow; Kubeflow; scikit-learn; PyTorch; TensorFlow; OpenTelemetry; SonarQube; and scientific, healthcare, laboratory, or regulated domains.
Benefits
- Standard Monday-Friday work schedule in an office environment.
- Equal opportunity employment with a stated commitment to building a diverse and inclusive workforce.
Tech Stack
AWSAzureFastAPIGitGoogle Cloud PlatformMLflowNumPyPandasPostgreSQLpytestPythonPyTorchscikit-learnSonarQubeTensorFlow
Categories
About Thermo Fisher Scientific
Thermo Fisher Scientific builds analytical instruments, lab equipment and consumables, specialty diagnostics, and provides pharma services (CDMO and clinical research) for biotech, pharma, academic, and healthcare customers. It earns revenue through product sales, e-commerce distribution (Fisher Scientific), and contract services under brands such as Thermo Scientific, Applied Biosystems, Invitrogen, Patheon, and PPD. Headquartered in Waltham, MA, it is publicly traded on the NYSE (TMO) and was created by the 2006 merger of Thermo Electron and Fisher Scientific.