AI Platform Architect

In this role, you will serve as the primary architect and visionary for a world-class AI ecosystem, bridging the gap between cutting-edge drug discovery and scalable cloud infrastructure. 

You will be responsible for designing and owning the end-to-end platform architecture on AWS and Databricks, ensuring that the autonomous AI agents being built are supported by robust, production-grade APIs and seamless MLOps workflows. By establishing the standards for data ingestion, model serving, and security, you will directly enable scientific breakthroughs that have the potential to transform global healthcare.

About the Company:

Our client is a world-renowned, commercial-stage biotech powerhouse leveraging high-scale AWS/Databricks ecosystems to build autonomous AI agents that will help accelerate life-saving drug discovery and launches.

*This role requires on-site presence 1x per week, on average. 

Key Responsibilities – Platform & Architecture

• Design and own the end-to-end AI platform architecture across AWS, Databricks, APIs, and frontend consumers
• Define standards for data ingestion, feature engineering, model training, serving, and monitoring
• Ensure platform scalability, reliability, security, and cost efficiency

ML & Data Platform

• Lead architecture and best practices for Databricks on AWS
• Implement data pipelines using Delta Lake (Bronze/Silver/Gold)
• Own MLflow setup for experiment tracking, model registry, and lifecycle management
• Enable batch and real-time inference workflows

Backend & API Layer

• Design and build production-grade APIs using FastAPI
• Define API contracts and integration patterns for frontend and downstream systems
• Implement authentication, authorization, rate limiting, caching, and observability
• Support low-latency inference and asynchronous workloads

Frontend Enablement

• Collaborate with frontend teams (React / Next.js) to deliver AI-powered user experiences
• Define API schemas and response patterns optimized for UI consumption
• Enable explainability, confidence scores, and model metadata where needed

MLOps & DevOps

• Establish CI/CD pipelines for models, APIs, and infrastructure
• Implement monitoring for model performance, data drift and quality, latency, errors, and uptime Enable safe deployments (blue/green, canary, rollback)

Security & Governance

• Ensure secure handling of PII and sensitive data
• Implement IAM best practices and secrets management
• Support auditability, model governance, and compliance requirements

Required Qualifications

• 7+ years of experience in software, data, or platform engineering
• 3+ years designing or operating ML/AI platforms in production
• Strong experience with AWS, Databricks, Delta Lake, MLflow, Python, and FastAPI
• Experience with LLMs / GenAI platforms
• Experience in regulated or enterprise environments
• Solid understanding of MLOps concepts and tooling

Equal Opportunity Statement

We are an equal opportunity employer and value diversity. They do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by applicable law.