Staff AI Engineer

As a Staff Engineer, you'll drive architecture and design for distributed systems that operate at scale, while still rolling up your sleeves as an IC. You'll work closely with product and business teams, mentor younger engineers, and solve 0-1 challenges that push both technology and the business forward. If you want to build, scale, and leave a tangible mark in healthcare AI, this role is for you.
Your responsibilities will span the following functions:
Technical Strategy and Architecture:
Define a technical roadmap for evolving from prompt-based systems to RAG and AI agents.
Drive architectural decisions for scalable, cost-effective Gen AI solutions in healthcare.
Oversee model evaluation, selection, and deployment strategies across multiple medical specialties.
Ensure technical debt management and maintainable code standards across the team.
Lead technical design reviews and architecture discussions.
Stay current with Gen AI research and translate innovations into product capabilities.
Product and Project Delivery:
Collaborate with Product, Clinical, and Business teams to translate requirements into technical solutions.
Manage project timelines, resource allocation, and delivery commitments for Gen AI initiatives.
Drive cross-functional collaboration to ensure seamless integration of AI capabilities.
Oversee A/B testing, experimentation, and data-driven decision making for AI features.
Ensure compliance with healthcare regulations (HIPAA) and coding standards (ICD-10 CPT).
Operational Excellence and Cost Management:
Implement monitoring, observability, and SLA management for production Gen AI systems.
Drive cost optimization initiatives for LLM usage, infrastructure, and data processing
Establish best practices for Gen AI MLOps, including model versioning and deployment pipelines.
Ensure system reliability, scalability, and performance optimization.
Lead incident response and post-mortem processes for AI system issues.
Strategic Planning:
Partner with leadership to define Gen AI strategy and competitive positioning.
Evaluate build vs buy decisions for Gen AI capabilities and tooling.
Drive innovation initiatives and proof-of-concept development for new AI applications.
Represent engineering in executive discussions about AI roadmap and investment priorities.
Requirements:
3+ years of hands-on experience with Deep Learning, Large Language Models, and Gen AI applications.
Deep understanding of RAG architectures, vector databases, and AI agent frameworks.
Experience with production Gen AI systems: deployment, monitoring, and cost optimization.
Knowledge of model evaluation, fine-tuning, and prompt engineering best practices.
Understanding of MLOps practices for LLM deployments and model lifecycle management.

Experience
9-13 yrs