Senior Software Engineer (Tech lead)

Thermo Fisher Scientific•Austin, TX

6d•Hybrid

About The Position

Thermo Fisher Scientific Inc. is seeking a Senior Software Engineer (Tech Lead) to join their team in Austin, TX. This role involves leading the design and implementation of AI application platform solutions, developing AI tools and web applications, and building/deploying microservices. The engineer will mentor junior staff, collaborate with cross-functional teams globally, and ensure high-quality software delivery through best practices in development, testing, and DevOps. The position requires a Master's degree in Computer Science or a related field, with 5 years of experience, or a Bachelor's degree with 7 years of experience. The role offers a hybrid work model and requires up to 10% domestic and international travel.

Requirements

Master’s degree or foreign degree equivalent in Computer Science, Computer Engineering, or related field of study.
5 years of experience as a Software Engineer, or related occupation.
Alternative: Bachelor’s degree or foreign degree equivalent in Computer Science, Computer Engineering, or related field of study plus 7 years of experience as a Software Engineer or related occupation.
Python, Java, TypeScript, Linux Shell.
AI Platform Architecture, Large Language Models (LLMs), GPT, Claude, Gemini, DALL·E, Agents, Function Calling, Model Context Protocol (MCP), RAG (Retrieval-Augmented Generation), Embedding Services, LangChain, AutoGen, SpringAI, OpenAI Assistant, OpenAI Agent, Code Interpreter.
OIDC, JWT, OAuth2, JSON, Swagger.
Angular, React, Node.js, HTML5, CSS, JavaScript, jQuery.
SpringBoot, Spring, JDBC, MicroServices, Maven, Tomcat.
Kubernetes, Docker, GitHub Actions, CI/CD, Ingress, Nginx, AWS (EKS, S3, SNS, SQS, RDS, Route53, Secret Manager, Cost Center), Azure (AI Hub, AI studio, Authentication, Cognitive AI Search), Load Balance, API Gateway, Helm Chart.
System Design, Domain-Driven Design (DDD), Test-Driven Development (TDD), Reactive Programming (WebFlux).
HTTP Streaming, WebSocket, Cookie, Session.
QA Automation, Unit Test.
Grafana, Prometheus, Metrics, Loki, JMeter, LangFuse.
PostgreSQL, Redis, Vector DB, Graph DB, Databricks.
VS Code, IntelliJ, GitHub Copilot, Confluence/Jira, Miro, Diagrams, Figma.

Responsibilities

Lead the design and implementation of AI application platform solutions, including system architecture, POCs, and solution documentation, using advanced technologies such as Agents, Function Calling, MCP, RAG, and large language models (LLMs).
Design and deliver AI tools and AI enabled web applications using React, Python, TypeScript and similar technologies ensuring performance, scalability, and maintainability.
Build, deploy, and maintain web applications & Microservices (Python & Java) for both on-premises and AWS Cloud environments.
Mentor junior and senior engineers, conduct code reviews and guide technical decisions to ensure high-quality software delivery.
Collaborate with cross-functional product development teams—scientists, engineers, and Product Development Managers (PDMs)—to gather requirements and craft interactive scientific and AI-driven software solutions.
Work closely with internal platform teams, including the Innovation team and Asia-Pacific teams (e.g., Korea, China) as well as the BLR (Bangalore) team, to coordinate cross-functional initiatives and drive AI integration strategies, with flexibility in working hours to support effective communication and collaboration across global and regional teams.
Help non-AI teams embed intelligent capabilities—such as agents and chatbots—into their platforms.
Maintain, support, and enhance existing software applications, ensuring they evolve with user needs and technical best practices.
Build and maintain automated test frameworks and tools, ensuring test coverage and reliability through standard QA practices.
Develop and manage CI/CD pipelines and continuous deployment technologies for rapid, reliable delivery, supporting both development and production environments.
Manage DevOps activities including Azure and AWS infrastructure, Kubernetes orchestration, Docker containerization, and Ingress configuration.
Ensure application-level security, cost efficiency, and observability through metrics and logging systems.
Attend and actively participate in all Agile Scrum ceremonies (Daily Stand-ups, PI Planning, Sprint Planning, Grooming, Retrospectives).
Support production release lifecycles including release planning, regression testing, go-live support, and post-release aftercare.
Create and maintain comprehensive code and system documentation to support current and future development.