Principal Engineer, Transformation Engineering

Mosaic Health

. Work with operational teams to understand workflows, handoffs, exceptions and data sources .

Posted 10/22/2026full-timeRemote • United StatesLead💰 $131,243 - $196,865 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying AI-enabled applications, with a strong focus on backend development using Python and TypeScript. Proficient in designing data pipelines and APIs, while ensuring adherence to engineering standards and best practices in cloud-native application development.

Highest-signal resume keywords

AI-Enabled Application DevelopmentBackend Development in Python and TypeScriptData Pipeline Design and OperationAPI Design and Database Schema DevelopmentCloud Infrastructure and Distributed Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonTypeScriptSQLAPI DesignData Pipeline DesignETL/ELTCloud InfrastructureMicroservicesCI/CDSoftware Architecture

Soft Skills

Analytical SkillsCommunication SkillsMentoring SkillsTechnical Leadership

Tools & Technologies

AI ModelsLanguage Model APIsObservability ToolsContainersData Validation Tools

Certifications & Qualifications

Bachelor's Degree in Computer ScienceSoftware EngineeringInformation Systems

Industry Keywords

AI-Assisted Software DevelopmentEngineering GovernanceData PrivacyEnterprise Application DesignResponsible AI Adoption

Tech Stack

Tools & technologies

CloudDistributed SystemsETLMicroservicesPythonSQLTypeScript

About the role

Key responsibilities & impact

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

What you’ll need

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