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Job Description Summary
Mosaic Health is seeking a hands-on engineer with strong applied AI experience and deep knowledge of technology infrastructure and data pipelines. This is a hands-on individual contributor role, not a people-management position. You will build applications, integrations and automated workflows across apree, CareMore and Millennium Physician Group. Your work will connect operational needs with dependable technical solutions that improve service, reduce manual effort and support the business.
You will take initiative and personally carry solutions from discovery through rapid prototyping, pilot deployment and value validation, then partner with IT, data and security teams to industrialize solutions approved to scale. You will spend a substantial portion of your time designing, writing, testing and troubleshooting code, including the data pipelines that support your applications. Success requires independent execution and close collaboration: you will seek input early, work constructively with operational, IT, data and security partners, and keep stakeholders informed.
You will focus on a prioritized set of initiatives, understand differences in workflows and systems across the businesses, and build reusable capabilities that can be adapted to local needs.
How will you make an impact & Requirements
WHAT YOU WILL DO
Work with operational teams to understand workflows, handoffs, exceptions and sources of data. Turn an agreed business objective into a practical technical plan, identify missing information, and drive the next steps without waiting for fully specified requirements.
Build, collaborate on, and maintain AI-enabled applications, backend services and integrations. Apply language models, retrieval-augmented generation, structured outputs and tool calling where they solve a defined operational problem.
Design and maintain data pipelines for ingesting, transforming, validating and delivering structured and unstructured data. Handle data quality, schema changes, retries, duplicate records and backfills, and make data lineage and failures traceable.
Prototype and evaluate models, frameworks and software tools. Compare AI-based approaches with conventional software and existing products, and recommend solutions based on measured quality, latency, cost, maintainability and operational fit.
Build evaluation datasets and automated tests for model outputs, retrieval quality and complete workflows.
Partner with IT, data and security teams across Mosaic Health on approved architecture, access, integrations and deployment. Build pilots within approved environments and, for solutions approved to scale, work with Technology to transition and industrialize them with appropriate identity and access controls, networking, secrets management, auditability and protection of sensitive information.
Collaborate with consultants and vendors while retaining hands-on ownership of your deliverables. Review designs and code, contribute directly to implementation, and ensure documentation and knowledge transfer allow you to maintain and extend the work.
Work with business owners and Finance partners on pilot rollout, user feedback and value validation. Establish the baseline and track adoption, cycle time, manual effort, error rates, and realized operational and financial value to determine whether the solution should scale.
WHAT YOU BRING
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 the ability to explain technical decisions, failures and improvements.
Evidence of personally taking a product or workflow from an initial idea through pilot deployment and value validation, with demonstrated ability to partner on industrialization and ongoing improvement, including integrating language models into real applications. Able to explain what you built, how you resolved obstacles, and how you supported the solution after launch.
Strong backend development skills in Python and/or TypeScript, proficiency in SQL, and experience designing APIs, services and database schemas.
Practical understanding of language model APIs, embeddings, retrieval-augmented generation, structured outputs and tool calling. Able to design workflows around model limitations and select the appropriate approach for the task.
Experience evaluating AI systems with representative datasets and measurable quality criteria, including retrieval accuracy, unsupported outputs, edge cases and regression testing. Able to balance quality, latency and cost.
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.
A record of taking initiative and delivering with limited day-to-day direction. Able to break ambiguous problems into manageable steps, make sound technical decisions, learn unfamiliar tools, and follow through on implementation and support. Recognizes when to seek input or escalate a dependency, bringing clear options and a recommended next step.
A collaborative working style: listens to frontline users, seeks and incorporates feedback, shares knowledge, and works respectfully across disciplines. Communicates progress and tradeoffs clearly, follows through on commitments, and helps partners resolve shared problems.
Hands-on experience designing and operating data pipelines, including ETL/ELT, batch and event-driven processing, orchestration, data validation and monitoring. Understands how source-system behavior, data freshness, lineage and schema changes affect downstream applications and AI outputs.
QUALIFICATIONS
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field required; advanced degree preferred.
5-7 years of progressive software engineering experience, including significant experience serving 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, including responsible AI adoption, code provenance, data privacy, software quality, and engineering governance.
Deep experience implementing and advancing full-stack observability capabilities, including application performance monitoring, distributed tracing, telemetry, logging, cloud monitoring, and operational analytics across complex production environments.
Proven ability to influence enterprise technology strategy, lead cross-functional engineering initiatives, establish technical standards, and build alignment across Product Management, Enterprise Architecture, Infrastructure, Platform Engineering, Information Security, and executive technology leadership.
Exceptional analytical, communication, mentoring, and technical leadership skills with demonstrated technical adaptability and experience evaluating, introducing, and operationalizing emerging software engineering technologies and industry best practices.
Compensation Range:
$131,243.00 to
$196,865.00 The anticipated base salary range represents the Company's good-faith estimate of the compensation it reasonably expects to pay for this position at the time of posting. Actual compensation will be determined based on factors including experience, skills, qualifications, geographic location, internal equity, and business needs.