Senior Software Engineer, AI and ML Platforms

Job description

Overview

By joining Bio-Techne, you’ll join a company with a powerful and positive purpose of enabling cutting‑edge research in Life Sciences and Clinical Diagnostics. Bio-Techne and all of its brands provide tools for researchers to further treat and prevent disease worldwide. Bio-Techne develops innovative software and instrumentation solutions that help scientists generate accurate, reproducible biological data at scale.

Pay Range: $132,400.00 - $217,600.00

This Senior Software Engineer role sits at the intersection of AI engineering, cloud‑native microservices, and enterprise SaaS platforms. You will lead the design and implementation of scalable backend services that power AI‑enabled features across Bio-Techne software products.

This role is ideal for an experienced engineer who enjoys owning architecture, mentoring others, and delivering production‑grade systems used in regulated scientific environments. This is a hybrid position based out of our San Jose, CA site.

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. This includes MLOps practices, data access governance, observability frameworks, and security controls, ensuring that POC work can be reliably promoted to production environments

Establish and maintain MLOps practices for model versioning, evaluation, monitoring, and retraining — ensuring AI services degrade gracefully and remain reliable over time

Collaborate with product management, scientists, and UX teams to translate scientific workflows into AI‑driven software capabilities

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

Document system architecture, APIs, and operational considerations for internal and cross‑functional stakeholders

Qualifications

Education & Experience: 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

Equivalent combination of relevant education and experience

Knowledge, Skills, and Abilities: Strong proficiency in Python, Java, or similar backend languages with hands‑on microservices experience

Demonstrated 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, 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 trade‑offs, and build new capabilities

Demonstrated ability to implement ML or information‑retrieval algorithms; not solely through high‑level frameworks (examples: custom retrieval, ranking and re‑ranking strategies, embedding and chunking approaches, evaluation pipelines, or inference‑time optimizations)

Demonstrated track record of designing and building novel systems or components, rather than primarily integrating off‑the‑shelf tools

Strong computer‑science fundamentals: data structures, algorithmic complexity

Preferred Qualifications: 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

Benefits

Competitive insurance benefits starting on day one: medical, dental, vision, life, short‑term disability, long‑term disability, pet, and legal and ID shield

401(k) plans, employee stock purchase plan (ESPP), Health Savings Account (HSA), Flexible Spending Account (FSA), and Dependent Care FSA

Career development opportunities: mentorship, promotional opportunities, training and development, tuition reimbursement, internship programs

Employee resource groups, volunteer paid time off, employee events, and charity drives

Accrued leave policy with paid holidays, paid time off, and paid parental leave

Culture of empowerment and innovation, where employees feel valued and encouraged to bring new ideas

Equal Employment Opportunity

Bio-Techne is an E-Verify Employer in the United States. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

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Worksite address

san jose, CA, 95199, US

Who can apply

Review the original listing for work authorization, qualifications and employer requirements.