Lead AI Platform Engineer — Remote MLOps & Scale

TetraScience; San Mateo (CA); On-site; USD 200,000 - 270,000; Full time

Benefits offered by this job

Employer-paid benefits for employees &

Unlimited PTO

401K

Remote work flexibility

Life Insurance

Coaching culture

Salary disclosed

Job summary

TetraScience is seeking a Lead Software Platform Engineer to own and scale our AI/ML data infrastructure. You will architect cloud-based services and MLOps tooling used by Applied AI, data engineering, and platform teams, guiding production-grade model, prompt, and agent workflows.

You will drive end-to-end lifecycle management, security, cost controls, and observability while mentoring engineers and setting platform standards for reproducibility and compliance.

Qualifications

• Proven track record architecting distributed, cloud-native AI platforms.
• Experience delivering multi-tenant AI infrastructure in production.
• Strong API-first design with scalable REST/OpenAPI services.
• Hands-on coding in TypeScript and Python for APIs and backends.

Responsibilities

• Own the architecture of the AI/ML platform and its API surface.
• Oversee end-to-end model lifecycle across multi-model serving.
• Design inference substrate for real-time and batch workloads.
• Integrate LLMs and agent ecosystems with secure, scalable tooling.
• Build observability, SLI/SLO, and production readiness metrics.
• Drive IaC and deployment automation across multi-tenant infra.
• Lead design reviews and mentor senior engineers.

Skills

Distributed systems

MLOps

API design

TypeScript

Python

Databricks MLflow

AWS

CI/CD

Security for multi-tenant

Leadership & mentoring

Tools

Databricks MLflow

AWS Bedrock

Docker

CloudFormation

AWS CDK

OpenAPI/REST

Job description

TetraScience is seeking a Lead Software Platform Engineer to own and scale our AI/ML data infrastructure. You will architect cloud-based services and MLOps tooling used by Applied AI, data engineering, and platform teams, guiding production-grade model, prompt, and agent workflows.

You will drive end-to-end lifecycle management, security, cost controls, and observability while mentoring engineers and setting platform standards for reproducibility and compliance.