Lead the design, development, deployment, and optimization of AI solutions
Ensure solutions are production-grade, secure, compliant, and capable of delivering meaningful client and operational impact.
Drive agile execution, and translating healthcare business needs into scalable AI technology and data solutions.
Design, architect, and deploy enterprise-ready AI agents.
Develop and manage multi-provider abstraction layers across AI platforms.
Build cloud-native AI systems, using Kubernetes, Docker, microservices, serverless computing, event-driven architectures, CI/CD, and comprehensive observability stacks.
Tailor and implement industry-specific agentic workflows.
Partner with cross-functional stakeholders to define use cases, rapidly prototype solutions.
Conduct design workshops, POCs, and joint engineering sessions.
Define and monitor key metrics for agent accuracy, safety, latency, cost-efficiency, and reliability.
Ensure AI solutions comply with applicable industry and regulatory standards.
Create and maintain detailed documentation across model development, training, fine-tuning, deployment, and operational processes.
Provide technical leadership, mentorship, and guidance to junior engineers.

Requirements

US Citizenship or a Green Card is required
Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related field.
A minimum of FIVE (5) years of engineering experience with cloud-native systems (APIs, microservices, containerization, serverless architectures).
A minimum of ONE (1) year of deep, hands-on experience designing and deploying agentic AI systems (RAG, orchestration, tool use, workflow automation) in production.
A minimum of THREE (3) years working with leading AI platforms (OpenAI, Claude, Vertex AI) and open-source LLM frameworks, including building abstraction layers for multi-provider pipelines.
A minimum of FIVE (5) years of programming experience in Python, Java, or equivalent languages, with familiarity in logging, monitoring, and agent/LLM observability.
A minimum of FIVE (5) years deploying production systems using CI/CD, infrastructure-as-code (Terraform, Helm), and modern monitoring/debugging tools.
Delivered 3 to 5 medium or large-scale AI/LLM projects of significant business value.
Strong command of Python and modern AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers).
Experience deploying and optimizing models using serving/inference frameworks (Triton, TensorRT, VLLM, TGI, etc.).
Familiarity with MLOps practices for CI/CD, continuous training, observability, and automated monitoring.
Understanding of healthcare interoperability standards (FHIR, HL7, EDI) and regulatory frameworks (HIPAA, SOC2) is preferred.
Experience with Voice AI and applied healthcare AI solutions is a plus.
Proven ability to work with business, engineering, and IT teams to incorporate AI/ML capabilities into enterprise solutions.
Strong analytical problem-solving skills and the ability to operate in ambiguous, fast-moving environments.
Excellent communication skills, enabling effective collaboration across internal and client teams.

Benefits

Medical, Rx, Dental & Vision Insurance
Personal and Family Sick Time & Company Paid Holidays
Position may be eligible for a discretionary variable incentive bonus
Parental Leave and Adoption Assistance
401(k) Retirement Plan
Basic Life & Supplemental Life
Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
Short-Term & Long-Term Disability
Student Loan PayDown
Tuition Reimbursement, Personal Development & Learning Opportunities
Skills Development & Certifications
Employee Referral Program
Corporate Sponsored Events & Community Outreach
Emergency Back-Up Childcare Program
Mobility Stipend

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI solutionscloud-native systemsmicroservicescontainerizationserverless architecturesPythonJavaTensorFlowPyTorchCI/CD

Soft Skills

technical leadershipmentorshipanalytical problem-solvingcommunicationcollaboration