MLops Engineer (Remote)

Join TetraScience, the Scientific Data and AI Cloud company, as a Lead Software Platform Engineer working at the intersection of distributed systems and MLOps. In this role, you will own and scale AI and data infrastructure that supports production-grade AI/ML workflows for scientists at some of the world's largest pharmaceutical companies.
This is a highly impactful opportunity for an engineer who has built AI/ML infrastructure as a multi-tenant product rather than internal tooling. You will serve as the technical design authority for AI platforms, model serving, LLMs, agents, observability, security, and evaluation frameworks while helping define the future direction of AI infrastructure in a regulated environment.

Required Skills & Experience
10+ years of professional experience in software engineering and infrastructure engineering designing, building, and scaling distributed cloud-native systems
Demonstrated experience as a technical leader or architect responsible for system design, scalability, performance, and cost optimization
Experience designing security into multi-tenant platforms, including handling sensitive data such as PII and PHI and mitigating LLM-specific risks
Extensive experience building and maintaining AI/ML infrastructure in production as a multi-tenant product with external users
Deep hands-on experience deploying and operating LLM-based systems including RAG architectures, retrieval and embedding design, prompt versioning, model versioning, and tool/function calling
Expert-level coding skills in TypeScript and Python for backend services and APIs
Production experience with model registry and serving platforms, ideally Databricks MLflow
Experience building AI evaluation frameworks, regression gates, and drift or quality monitoring capabilities
Experience designing scalable, secure, versioned APIs using REST and OpenAPI specifications
Strong AWS and containerization experience, including Docker
Experience with CloudFormation or AWS CDK and contributing to deployment automation and CI/CD processes
Experience defining observability practices including monitoring, alerting, logging, distributed tracing, and SLI/SLO/SLA models
Ability to influence technical direction, communicate with customers and cross-functional teams, and mentor engineers

Desired Skills & Experience
Familiarity with emerging LLM frameworks for advanced prompt orchestration and programmatic LLM pipelines
Experience running agentic or multi-step orchestration in production
Experience with MCP as an integration surface for tooling and non-human identities
Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments
Experience with multimodal model inputs including image and instrument data
Experience with fine-tuning, distillation, quantization, batching, KV-cache strategies, or other model optimization techniques
Experience delivering AI/ML systems in regulated environments including GxP, 21 CFR Part 11, or SOC 2 environments
Background in scientific, life sciences, or laboratory data domains
What You Will Be Doing
Tech Breakdown
AI/ML Platform Architecture
[Confirm: percentage] LLMs, Agents, and RAG Systems
[Confirm: percentage] AWS Infrastructure & Cloud Services
[Confirm: percentage] Model Lifecycle Management & MLflow
[Confirm: percentage] Security, Observability, and Compliance
Daily Responsibilities
Designing and scaling AI/ML platform architecture
Building model-serving and agent infrastructure
Developing evaluation, observability, and governance capabilities
Partnering with Applied AI, Data Engineering, Security, and Platform teams
Technical leadership, architecture reviews, and mentoring
The Offer
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