Lead Software Platform Engineer, MLOps

TetraScience is the Scientific Data and AI Cloud company, catalyzing the Scientific AI revolution by designing and industrializing AI-native scientific data sets. We are the category leader in this vital new market, generating more revenue than all other companies in the aggregate.

In connection with your candidacy, you will be asked to review the Tetra Way letter, authored by Patrick Grady, our co-founder and CEO. This letter is designed to assist you in understanding whether TetraScience is the right fit for you from a values and ethos perspective.

The Role:

We're looking for a Lead Software Platform Engineer working at the intersection of distributed systems and MLOps. You will own and scale our AI and data infrastructure as a product our customers build their science on, and that every other engineering team builds against. You will architect the cloud-based services and MLOps infrastructure that enable production-grade AI/ML workflows, working closely with Applied AI engineers, data engineers, and platform teams.

What You Will Do:

• Own the technical architecture of the AI/ML platform: the service and API surface our customers use to run models and agents against their own scientific data.
• Own the end-to-end model and prompt lifecycle across Databricks MLflow and AWS Bedrock.
• Design the inference substrate for both real-time and batch AI workloads.
• Integrate AI models and large language models (LLMs) into production systems.
• Design security into the AI platform, partnering with our security team.
• Build the evaluation and quality infrastructure that makes AI shippable.
• Establish observability for the AI platform.
• Design for reproducibility and lineage required in a validated pharma environment.
• Contribute to the infrastructure-as-code and deployment automation for the AI platform.
• Own production readiness for the AI platform with Applied AI engineers, data engineers, and platform teams.
• Act as SME and design authority across product and engineering.
• Lead design reviews and mentor senior and mid-level engineers.
• Set technical direction on emerging AI infrastructure.

Qualifications:

• 10+ years of professional experience in software engineering and infrastructure engineering.
• Demonstrated experience as a technical leader or architect.
• Experience designing security into a multi-tenant platform.
• Extensive experience building and maintaining AI/ML infrastructure in production.
• Deep, hands-on experience taking LLM-based systems to production.
• Expert-level coding skills in TypeScript and Python.
• Production-level experience with a model registry and serving stack.
• Experience treating AI evaluation as a release gate.
• Proficiency in API-first design.
• Solid working knowledge of AWS and containerized workloads.
• Experience defining observability and SLI/SLO/SLA practice for production systems.
• Ability to articulate ideas clearly to customers and cross-functional teams.

Nice to Have:

• Familiarity with emerging LLM frameworks.
• Experience running agentic or multi-step orchestration in production.
• Understanding of LLM cost monitoring and latency optimization.
• Experience with multimodal model inputs.
• Experience with fine-tuning, distillation, or model optimization.
• Experience delivering ML or AI systems in a regulated environment.
• Background in scientific, life sciences, or laboratory data domains.

100% employer-paid benefits for all eligible employees and immediate family members. Unlimited paid time off (PTO). 401K. Flexible working arrangements - Remote work. Company paid Life Insurance, LTD/STD. A culture of continuous improvement where you can grow your career and get coaching.

The salary range for this position is $200K-$270K USD. Final compensation is determined by a thorough evaluation of factors including the candidate’s specific experience, localized market data, and internal team equity. We are not currently providing visa sponsorship for this position.