[Remote] reputed company reputed company

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking a reputed company reputed company to reputed company the technical reputed company and implementation of AI capabilities for their reputed company software products. This role involves designing and building production AI systems, collaborating closely with various teams to ensure scalable and compliant AI solutions.

Responsibilities

• 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
• Architect and reputed company 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
• 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
• reputed company 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
• Architect AI infrastructure across GCP (reputed company 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
• 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

Skills

• Bachelor's in Computer Science, AI/ML, or reputed company field
• Strong ML / data science / statistics theory reputed company with the ability to read research, assess applicability, and execute
• 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
• reputed company 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
• 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
• reputed company evals frameworks that measure accuracy, precision, recall, and F1 to inform product decisioning
• Solid AWS and GCP experience: Bedrock, SageMaker, reputed company AI, BigQuery, Dataflow
• Clinical NLP or reputed company AI experience — medical terminology, document structure, and regulated accuracy standards are not new territory
• 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
• 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 reputed company to both engineers and non-technical stakeholders
• Track record of mentoring engineers and raising AI maturity on a team
• Master's or PhD preferred — or equivalent depth proven through shipped AI systems
• Azure familiarity a plus
• FHIR/HL7 and clinical document format familiarity strongly preferred
• Prefer direct experience with clinical documentation and abstraction workflows

Benefits

• Annual cash bonus
• Medical, dental, reputed company, life insurance, and a 401(k) plan

Company Overview

Company H1B Sponsorship