Principal Engineer, Transformation Engineering

Job not on LinkedIn

🔥 4 minutes ago

🇺🇸 United States – Remote

💵 $131.2k - $196.9k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

👻 Ghost score 0%

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Mosaic Health

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🏥 Healthcare

👥 B2C

Healthcare • B2C

Mosaic Health is a national care delivery platform focused on expanding access to comprehensive primary care for consumers covered by Commercial, Individual Exchange, Medicare, and Medicaid health plans. It brings together multiple operating units and brands (including CareMore Health, Millennium Physician Group/MPG, Castlight Health, Vera Whole Health, and apree health) to deliver coordinated primary care services and related care-management capabilities across payer types. Mosaic Health’s corporate site and leadership roster reflect a centralized platform structure with executive leadership overseeing business units and strategic partnerships.

📋 Description

• Work with operational teams to understand workflows, handoffs, exceptions and data sources • Turn business objectives into practical technical plans and drive next steps • Build, collaborate on, and maintain AI-enabled applications, backend services and integrations • Apply language models, retrieval-augmented generation, structured outputs and tool calling to operational problems • Design and maintain data pipelines for ingesting, transforming, validating and delivering structured and unstructured data • Prototype and evaluate models, frameworks and software tools • Build evaluation datasets and automated tests for model outputs, retrieval quality and complete workflows • Partner with IT, data and security teams on architecture, access, integrations and deployment • Build pilots and transition approved solutions to industrialized production environments • Collaborate with consultants and vendors while retaining hands-on ownership of deliverables • Review designs and code, contribute directly to implementation, and ensure documentation and knowledge transfer • Work with business owners and Finance partners on pilot rollout, user feedback and value validation • Track adoption, cycle time, manual effort, error rates, and operational and financial value

🎯 Requirements

• Typically, 5-7 years of software engineering experience, including substantial hands-on experience building and deploying AI-enabled applications • Demonstrated ownership of production systems and ability to explain technical decisions, failures and improvements • Evidence of taking a product or workflow from initial idea through pilot deployment and value validation • Strong backend development skills in Python and/or TypeScript • Proficiency in SQL • Experience designing APIs, services and database schemas • Practical understanding of language model APIs, embeddings, retrieval-augmented generation, structured outputs and tool calling • Experience evaluating AI systems with representative datasets and measurable quality criteria • Deep understanding of cloud infrastructure and distributed applications, including compute, storage, networking, identity and access management, containers, queues, observability and CI/CD • Experience diagnosing production issues and making reliability, security and cost tradeoffs • Hands-on experience designing and operating data pipelines, including ETL/ELT, batch and event-driven processing, orchestration, data validation and monitoring • Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field required • 5-7 years of progressive software engineering experience, including significant experience as a technical lead, software architect, or principal engineer responsible for enterprise-scale software platforms • Expert-level knowledge of software architecture, distributed systems, cloud-native application development, microservices, API design, engineering automation, CI/CD, secure software development, and enterprise application design • Demonstrated expertise establishing engineering standards for AI-assisted software development, responsible AI adoption, code provenance, data privacy, software quality, and engineering governance • Deep experience implementing and advancing full-stack observability capabilities • Proven ability to influence enterprise technology strategy and lead cross-functional engineering initiatives • Exceptional analytical, communication, mentoring, and technical leadership skills