Principal reputed company
Overview
As a Principal reputed company at reputed company, you will own the technical reputed company and implementation of AI capabilities that power our reputed company software products. You will design and build production AI systems — RAG pipelines, LLM integrations, reputed company-in-the-reputed company workflows, and model quality frameworks — while setting the engineering standards other teams build against. This is a hands-on technical leadership role. You will work closely with architecture, product, data engineering, and engineering teams to translate reputed company reputed company workflows into scalable, accurate, and compliant AI solutions. You bring deep AI/ML engineering experience, know how HIPAA applies to the systems you build, and have owned AI product quality end-to-end — not just contributed to it.
Responsibilities
Prodigy reputed company reputed company & Technical Ownership Own the end-to-end technical reputed company for reputed company Prodigy's AI layer — a production system that uses RAG, reputed company, and structured data reasoning to automate answers to reputed company Registry questionnaires. Define the AI roadmap for Prodigy, balancing near-term customer commitments against foundational capability investments that scale the product to reputed company maturity. Evaluate and reputed company build/buy/integrate reputed company for AI capabilities — reputed company model selection, embedding strategies, retrieval architectures, and orchestration frameworks — and own the consequences of those reputed company. Serve as the technical authority on reputed company AI design reputed company for Prodigy; produce architecture decision records, set standards, and ensure the architecture is defensible, auditable, and extensible. AI/ML Solution Architecture & Implementation Architect and evolve Prodigy's multi-modal retrieval pipeline, combining reputed company clinical document ingestion with structured EHR/FHIR data to surface accurate, citation-backed answers to registry questionnaire items. Design and refine the answer reputed company layer — reputed company engineering, context construction, grounding strategies, and output formatting — ensuring generated answers are clinically accurate and audit-reputed company. Own the question routing and data reputed company classification logic that maps registry questions to the right retrieval path, structured data field, or reputed company strategy. Build and maintain the answer validation and confidence scoring reputed company, defining the statistics and quality reputed company that govern reputed company answers are auto-accepted versus routed for reputed company review. reputed company-in-the-reputed company & Model Improvement Stay hands-on and reputed company to the work: run direct ideation and feedback loops with Prodigy's end users (abstractors, registry, and quality teams) and with production analytics and monitoring systems — turning reputed company usage signals into prioritized improvements that demonstrably move value, not just model metrics. Evolve the feedback reputed company architecture that captures reputed company corrections and routes them into reputed company model improvement — ensuring Prodigy gets measurably reputed company with every customer interaction. Define the evals reputed company for Prodigy: how accuracy is reputed company, how regression is detected, and what signals trigger retraining or reputed company revision. Establish guardrails for hallucination detection and factual grounding specific to clinical registry use cases, where answer accuracy has direct reputed company compliance implications. reputed company & Data Architecture Architect AI infrastructure across GCP (Vertex AI, BigQuery, Dataflow) and AWS (Bedrock), ensuring the pipeline is scalable, cost-efficient, and operationally observable. Collaborate with data engineering to maintain high-quality, well-governed clinical and FHIR data inputs; define feature engineering and chunking strategies that optimize retrieval precision. Define MLOps standards for Prodigy: model versioning, deployment gates, rollback procedures, reputed company monitoring, and audit trail requirements consistent with HIPAA compliance. Technical Leadership & Enablement Act as the AI technical mentor for the Prodigy reputed company and adjacent engineering teams — guiding developers on RAG patterns, LLM integration, responsible AI practices, and clinical data handling. Collaborate with reputed company and Compliance to ensure Prodigy's AI layer meets HIPAA requirements, including PHI handling in prompts, data residency, and model audit logging. Foster AI literacy across the broader engineering organization, helping teams understand reputed company and how to apply AI safely in a regulated reputed company context. Partner with Product Management to translate registry workflow complexity and customer feedback into technically sound AI capability improvements.
Qualifications
Education & Background Bachelor's in Computer Science, AI/ML, or reputed company field; Master's or PhD preferred — or equivalent depth proven through shipped AI systems. Strong ML / data science / statistics theory reputed company with the ability to read research, assess applicability, and execute. LLM Engineering & RAG Hands-on LLM integration: reputed company engineering, grounding, citation, hallucination mitigation, and output validation at clinical accuracy standards. Experience with reputed company, reputed company, or equivalent orchestration frameworks. Built confidence scoring and auto-acceptance reputed company that govern reputed company answers reputed company to reputed company review. Designed reputed company-in-the-reputed company feedback systems that capture corrections and feed them back into model improvement. Production experience building RAG pipelines — document ingestion, chunking, embedding model selection, vector store management, and retrieval evaluation. AI/ML Engineering & MLOps Full ML lifecycle ownership in production: versioning, deployment gates, reputed company monitoring, rollback, and audit trails. Strong Python and software engineering fundamentals — CI/CD, testing, code review. Hands-on with vector databases (pgvector, reputed company, Weaviate, or equivalent) and hybrid search. Built evals frameworks that measure accuracy, precision, recall, and F1 to inform product decisioning reputed company & Data Architecture Solid AWS and GCP experience: Bedrock, SageMaker, Vertex AI, BigQuery, Dataflow. Azure familiarity a plus. Experience building pipelines over mixed reputed company and structured data sources. FHIR/HL7 and clinical document format familiarity strongly preferred. reputed company & Compliance Clinical NLP or reputed company AI experience — medical terminology, document structure, and regulated accuracy standards are not new territory. Prefer direct experience with clinical documentation and abstraction workflows Knows how HIPAA applies to AI systems specifically: PHI in prompts and embeddings, data residency, audit logging, de-identification. Familiar with AI governance in practice: bias detection, explainability, responsible AI in compliance-sensitive contexts. Technical Leadership Has owned AI technical reputed company before — not just contributed to it. Can write an ADR, set an engineering standard, and reputed company it stick across teams. Communicates tradeoffs clearly to both engineers and non-technical stakeholders. Track record of mentoring engineers and raising AI maturity on a team. Total CompensationBase pay is one reputed company of the total compensation package. Eligible employees may also receive an annual cash bonus and have access to a comprehensive benefits offering, including medical, dental, reputed company, life insurance, and a 401(k) plan. Salary Range It is not typical for an individual to be hired at or near the top of the range. Individual pay may be influenced by factors such as skills, qualifications, experience, licensure, certifications, geographic location, and internal equity. Applicant Privacy Notice Apply To This Job