Responsibilities
- Model Productionization: Lead the engineering efforts to take cutting-edge data science models from research and development to scalable, production-ready systems, ensuring robustness, performance, and reliability.
- Agentic AI Development: Design, develop, and deploy intelligent AI agents and multi-agent systems using frameworks like Google ADK, LangChain, and LangGraph. These agents will automate complex clinical and administrative workflows, such as detecting missed HCC codes, surfacing quality gaps, prompting compliant CPT submissions, and automating patient outreach.
- System Architecture: Contribute to the architectural design of our AI-driven operating system, focusing on modularity, scalability, and integration points for AI services within our broader platform.
- MLOps & Infrastructure: Implement and champion MLOps best practices for continuous integration, deployment, monitoring, and optimization of AI models and agent behaviors in a real-time clinical environment.
- Performance & Reliability: Ensure the high performance, low latency, and fault tolerance of AI agents and inference pipelines, critical for real-time decision support and automated actions.
- Cross-Functional Collaboration: Work closely with data scientists, clinical domain experts, product managers, and other engineering teams to translate complex clinical problems into AI solutions and integrate them seamlessly into the Arbiter platform.
- Mentorship & Innovation: Actively mentor junior AI engineers, contribute to our internal knowledge base, and stay abreast of the latest advancements in AI, machine learning, and agentic systems to continuously innovate our offerings.
- Hiring & Onboarding: Participate in interviewing and onboarding new team members, helping to grow a world-class AI engineering organization.
Basic qualifications
- 8+ years of deep, hands-on experience in AI Engineering, Machine Learning Engineering, MLOps, or a closely related field, with a strong focus on productionizing models.
- Exceptional proficiency in Python for building complex AI systems and data pipelines.
- Demonstrated experience designing, building, and deploying AI agents and multi-agent systems using frameworks like LangChain, LangGraph, or similar agent orchestration tools.
- Profound understanding and hands-on experience with cloud-native AI/ML platforms, especially Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery ML, Dataflow).
- Strong knowledge of MLOps principles, including CI/CD for ML, model monitoring, versioning, and explainability.
- Solid understanding of machine learning algorithms, model training, evaluation, and inference.
- Intimate knowledge of and ability to implement unit, integration, and functional testing strategies.
- Experience providing technical leadership and guidance, and thinking strategically and analytically to solve problems.
- Friendly communication skills and ability to work well in a diverse team setting.
- Demonstrated experience working with many cross-functional partners.
- Demonstrated experience leading a software product or component vision and delivery plan.
Preferred qualifications
- Familiarity with Google ADK for AI development and deployment.
- Direct experience working with Large Language Models (LLMs) and their application in real-world systems.
- Experience in the healthcare, life sciences, or other highly regulated industries, especially with clinical data (EMRs, claims, patient outcomes).
- Proven track record of building autonomous or semi-autonomous AI systems that operate with human-in-the-loop oversight.
- Experience with unstructured data processing (e.g., natural language processing for clinical notes).
- Contributions to open-source AI/ML projects or relevant publications.
- Highly Competitive Salary & Equity Package: Designed to rival top FAANG compensation, including meaningful equity.
- Generous Paid Time Off (PTO): To ensure a healthy work-life balance.
- Comprehensive Health, Vision, and Dental Insurance: Robust coverage for you and your family.
- Life and Disability Insurance: Providing financial security.
- Simple IRA Matching: To support your long-term financial goals.
- Professional Development Budget: Support for conferences, courses, and certifications to fuel your continuous learning.
- Wellness Programs: Initiatives to support your physical and mental health.
Tags & focus areas
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