Senior Software Engineer, AI and ML Platforms
$132,400–$217,600 year
Hybrid · San Jose, California, United States
Job Summary
Senior Software Engineer will lead the design and implementation of cloud-native microservices-based backend systems powering AI-enabled features across Bio-Techne software products. You will build AI-powered services including LLM-based assistants, recommendations, and automation workflows, develop scalable REST and event-driven APIs, architect and implement RAG pipelines over scientific data, and ensure reliability, observability, security, and performance in production. You will establish and maintain MLOps practices for model versioning, evaluation, monitoring, and retraining; mentor junior engineers and participate in design/code reviews; collaborate with product management, scientists, and UX teams to translate scientific workflows into AI-driven software capabilities; and drive technical standards for code quality and system architecture.
Required Qualifications
- B.S. in Computer Science, Software Engineering, or related technical field and 7+ years of relevant experience developing and operating production-grade software systems
- M.S. in Computer Science, AI/ML, or related discipline and 5+ years of relevant experience
- Or equivalent combination of relevant education and experience
- Strong proficiency in Python, Java, or similar backend languages with hands-on microservices experience
- Experience designing and operating cloud-native SaaS platforms
- Experience building RESTful APIs using frameworks such as FastAPI, Flask, or Spring Boot
- Hands-on experience integrating AI/ML or LLM-based services into real-world applications
- Solid understanding of distributed systems, asynchronous processing, and service-to-service communication
- Experience with containerization (Docker) and CI/CD pipelines
- Strong written and verbal communication skills across engineering and scientific teams
- Demonstrated ability to implement ML or information-retrieval algorithms (e.g., retrieval, ranking, embeddings, evaluation pipelines)
- Demonstrated track record of designing and building novel systems or components
- Strong computer-science fundamentals: data structures, algorithmic complexity
- Preferred: experience with AWS/Azure, Kubernetes, vector databases (pgvector, FAISS, Pinecone), LangChain or LlamaIndex, RAG frameworks, and experience in regulated environments (GxP)
- Experience designing multi-tenant SaaS systems and license-based features
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