About TetraScience

TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft.

In connection with your candidacy, you will be asked to carefully review “The Tetra Way,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you.

What You will Do

We’re looking for a Senior AI Platform Engineer to help design, build, and scale our AI and data infrastructure. In this role, you’ll focus on architecting and maintaining cloud-based MLOps pipelines to enable scalable, reliable, and production-grade AI/ML workflows, working closely with AI engineers, data engineers, and platform teams. Your expertise in building and operating modern cloud-native infrastructure will help enable world-class AI capabilities across the organization.

If you are passionate about building robust AI infrastructure, enabling rapid experimentation, and supporting production-scale AI workloads, we’d love to talk to you.

• Design, implement, and maintain cloud-native platform to support AI and data workloads, with a focus on AI and data platforms such as Databricks and AWS Bedrock.
• Build and manage scalable data pipelines to ingest, transform, and serve data for ML and analytics.
• Develop infrastructure-as-code using tools like Cloudformation, AWS CDK to ensure repeatable and secure deployments.
• Collaborate with AI engineers, data engineers, and platform teams to improve the performance, reliability, and cost-efficiency of AI models in production.
• Drive best practices for observability, including monitoring, alerting, and logging for AI platforms.
• Contribute to the design and evolution of our AI platform to support new ML frameworks, workflows, and data types.
• Stay current with new tools and technologies to recommend improvements to architecture and operations.
• Integrate AI models and large language models (LLMs) into production systems to enable use cases using architectures like retrieval-augmented generation (RAG).

Requirements

• 7+ years of professional experience in software engineering and infrastructure engineering.
• Extensive experience building and maintaining AI/ML infrastructure in production, including model, deployment, and lifecycle management.
• Expert-level coding skills in TypeScript and Python building robust APIs and backend services.
• Production-level experience with Databricks MLFlow, including model registration, versioning, asset bundles, and model serving workflows.
• Expert level understanding of containerization (Docker), and hands on experience with  CI/CD pipelines, orchestration tools (e.g., ECS) is a plus.
• Proven ability to design reliable, secure, and scalable infrastructure for both real-time and batch ML workloads.
• Strong knowledge of AWS and infrastructure-as-code frameworks, ideally with CDK.
• Ability to articulate ideas clearly, present findings persuasively, and build rapport with clients and team members. 
• Strong collaboration skills and the ability to partner effectively with cross-functional teams.

Nice to Have

• Familiarity with emerging LLM frameworks for advanced prompt orchestration and programmatic LLM pipelines.
• Understanding of LLM cost monitoring, latency optimization, and usage analytics in production environments.
• Knowledge of vector databases / embeddings stores (e.g., OpenSearch) to support semantic search and RAG.

Benefits

Benefits

• 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 $170K-$220K USD. The salary range posted reflects our target baseline for this role. 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.