Senior AI Engineer
WHO WE ARE
JOB SUMMARY
DUTIES & RESPONSIBILITIES
- Lead the end-to-end delivery of complex AI products including agentic workflows, RAG systems, and services.
- Collaborate with Product, Engineering, Data, and clinical and operational teams.
- Translate stakeholder needs into validated, access-aware AI workflows with clear system behavior, acceptance criteria, risk controls, and delivery trade-offs.
- Design AI workflow and RAG product lines, including ingestion, retrieval quality, attribution, confidence handling, agent tools, and human-review paths.
- Implement workflows with reliable AI control layers and optimize healthcare AI models across prompting, retrieval, reranking, fine-tuning, and model-selection approaches.
- Own healthcare AI evaluation and release frameworks, including adversarial testing, regression thresholds, release gates, and production telemetry.
- Provide senior technical leadership through design and code reviews, incident response, mentoring, and reusable engineering improvements.
- Deliver healthcare AI services using approved cloud capabilities and HITRUST-aligned controls for PHI/PII, security, privacy, auditability, responsible AI, and compliance.
EDUCATION, TRAINING, AND PROFESSIONAL EXPERIENCE
- Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Science, Linguistics, or a related field; equivalent practical experience may be considered.
- Typically, 5+ years of relevant engineering experience, including ownership of complex production components or technical leadership of feature delivery.
- Hands-on experience delivering and operating production or near-production AI/ML/LLM-enabled applications.
- Strong software engineering expertise in service and data-contract design, testing, CI/CD, observability, debugging, reliability, and operational support.
- Strong proficiency in Python, Java, Scala, C#, TypeScript or a comparable modern language.
- Deep working knowledge of structured outputs, RAG, tool use, evaluations, guardrails, monitoring, and human-in-the-loop design.
- Experience with cloud services and data-intensive systems; ability to collaborate across structured-data products and unstructured-data pipelines.
- Demonstrated self-directed exploration of emerging AI capabilities through independently built prototypes, tools, experiments, or applications.
- Experience translating AI experimentation into production solutions for enterprise or regulated environments, with attention to safety, reliability, security, governance, and measurable outcomes.
PREFERRED EXPERIENCE
- Healthcare experience involving PHI/PII, clinical or operational workflows, payer/provider operations, auditability, safety review, compliance controls, or value-based care.
- Experience with cloud AI and data platforms such as Azure, AWS, GCP, Databricks, Agent Bricks, Genie, Azure AI Foundry/Azure OpenAI, Azure ML, AKS/Kubernetes, OpenTelemetry, or AI observability and evaluation tooling.
- Model benchmarking, selection, adaptation, fine-tuning, reranking, or other domain-model optimization techniques.
- Experience leading technical initiatives across teams or mentoring several engineers.
As an Equal Opportunity Employer, we welcome and employ a diverse employee group committed to meeting the needs of NeueHealth , our consumers, and the communities we serve. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.
Originally posted on Himalayas
Not included in the source posting: benefits.
Skills
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