Senior Software Engineer, AI and ML Platforms

Responsibilities

• Lead the design and development of cloud-native, microservices-based backend systems supporting Bio-Techne software products
• Design, build, and deploy AI-powered services, including LLM-based assistants, recommendations, and automation workflows
• Develop scalable REST and event-driven APIs that integrate AI services with instrument software and customer-facing applications
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines over scientific, operational, and customer data
• Partner with central IT, Enterprise Data, and Infrastructure teams to align AI services with shared platform standards
• Establish and maintain MLOps practices for model versioning, evaluation, monitoring, and retraining
• Ensure reliability, observability, security, and performance of distributed services operating in production environments
• Drive technical standards for code quality, service ownership, and system architecture
• Mentor junior engineers and contribute to design reviews, code reviews, and technical decision-making

Requirements

• Strong proficiency in Python, Java, or similar backend languages with hands-on microservices experience
• 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, including experience working across engineering and scientific teams
• Strong ability to understand how systems work under the hood, with the ability to reason about and implement the underlying algorithms, evaluate the tradeoffs, and build new capabilities
• Demonstrated ability to implement ML or information-retrieval algorithms; not solely through high-level frameworks
• Experience with cloud platforms such as AWS or Azure
• Familiarity with Kubernetes and multi-service deployment strategies
• Experience managing the ML lifecycle, including but not limited to EDA, feature engineering, model training/tuning, validation, deployment, and maintenance
• Experience with vector databases (pgvector, FAISS, Pinecone, or similar)
• Experience with RAG frameworks such as LangChain or LlamaIndex
• Exposure to scientific software, laboratory instrumentation, or regulated environments (GxP)
• Experience designing systems with multi-tenant SaaS considerations and feature-based licensing

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
• Or, M.S. in Computer Science, AI/ML, or related discipline and 5+ years of relevant experience
• Or, equivalent combination of relevant education and experience

Pay

$132,400.00 - $217,600.00

Schedule

Hybrid position based out of San Jose, CA