Staff AI Solutions Engineer

Included Health

Hands-on Staff AI Solutions Engineer at Included Health designing AI tools to enhance productivity in healthcare. Collaborating with various teams to ensure compliance and security in healthcare solutions.

Posted 7/22/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying LLM-based solutions, with a strong focus on technical strategy, architecture, and governance for AI services. Proven ability to lead cross-functional initiatives, optimize model performance, and ensure compliance in regulated environments.

Highest-signal resume keywords

LLM Lifecycle ManagementPython ProgrammingAPI Integration (REST/GraphQL)Infrastructure as Code (Terraform)Cloud Deployment (GCP/AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringSystems IntegrationModel Performance EvaluationHuman-in-the-Loop ControlsArchitectural TradeoffsEngineering StandardsModel OptimizationCI/CD PracticesSecurity Best PracticesData Handling Patterns

Soft Skills

Strong CommunicationCollaborationConflict ResolutionInfluencing StakeholdersDetail Oriented

Tools & Technologies

CI/CD ToolingObservability ToolsSaaS ApplicationsOktaGoogle WorkspaceSlackJiraConfluenceJamf

Industry Keywords

Healthcare ComplianceRegulated EnvironmentsTechnical LeadershipCross-Functional InitiativesOperational Rigor

Tech Stack

Tools & technologies

AWSCloudCyber SecurityGoogle Cloud PlatformGraphQLJamfJavaScriptPythonTerraformTypeScript

About the role

Key responsibilities & impact

Design, build, deploy, and maintain production LLM‑based solutions and agent workflows.
Own the technical strategy and reference architecture for enterprise AI solutions across multiple teams and business functions.
Lead high-complexity, cross-functional AI initiatives from ambiguous problem definition through production adoption and measurable business outcomes.
Define and evolve reusable platform capabilities, implementation standards, and governance patterns that enable safe, scalable AI adoption beyond a single team.
Review citizen developer AI agents / solutions to provide recommendations for optimization, ensure compliance with guidelines and measure value.
Influence roadmap and investment decisions across the company through technical leadership and business-value analysis.
Drive technical debates, align stakeholders on tradeoffs, and unblock multi-team execution for strategically important AI initiatives.
Implement, review, and validate code produced by models; write production‑quality code and run code reviews to ensure correctness and security.
Build robust integrations and connectors (MCP, REST/GraphQL APIs, webhooks, SDKs, CLIs) between AI tooling and enterprise SaaS (e.g., Okta, Google Workspace, Slack, Jira, Confluence, Jamf).
Own end‑to‑end deployment and lifecycle for AI services: CI/CD pipelines, Infrastructure as Code modules (Terraform), cloud deployment (GCP/AWS), monitoring, and incident/runbook playbooks.
Establish and operate model evaluation, monitoring, and governance: accuracy and safety metrics, hallucination detection, drift monitoring, telemetry, alerting, and human‑in‑the‑loop controls.
Lead vendor evaluations and POCs across commercial and open‑source LLM/agent platforms; produce comparative performance, risk, and TCO recommendations to inform adoption.
Partner with Cybersecurity and Compliance to design PHI‑safe data handling patterns (sanitization, tokenization, least‑privilege access, audit logging) and ensure AI solutions align with relevant controls and policies.
Create and maintain architecture diagrams, API documentation, runbooks, support documentation, and onboarding materials so solutions are maintainable and auditable.
Mentor engineers and influence architectural standards for AI/LLM adoption across Digital Workplace; contribute reusable libraries and IaC modules to accelerate future builds.
Drive automation of operational tasks (provisioning, onboarding, common workflows) via agents and workflow tooling to reduce manual processes.
Partner with Technology Services leadership to implement AI spend management tools and value tracking.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
8+ years professional software engineering / systems integration experience.
Practical experience owning the complete lifecycle of LLMs and agent
Experience evaluating model performance, mitigating hallucinations and bias, and implementing human‑in‑the‑loop controls.
Ability to define reference architectures and reusable patterns for AI services used across multiple teams.
Experience making architectural tradeoffs across reliability, latency, cost, security, and maintainability in production systems.
Experience establishing engineering standards, guardrails, and paved-road patterns for AI development and deployment.
Experience optimizing model/runtime cost, usage controls, and value measurement.
Strong coding experience in Python and/or TypeScript/JavaScript with production software engineering discipline (code reviews, testing, CI/CD).
Experience designing and building API integrations (REST/GraphQL), webhooks, and custom connectors to SaaS applications.
Experience with Infrastructure as Code (Terraform) and deploying services to cloud platforms (GCP/AWS).
Familiarity with CI/CD tooling and observability best practices (metrics, logs, tracing).
Working knowledge of security best practices for data‑sensitive systems and experience collaborating with Security & Compliance teams. Experience in healthcare or other regulated environments is strongly preferred.
Strong communicator and collaborator who can translate ambiguous business needs into technical designs and influence cross‑functional stakeholders.
Bias for action: ability to move quickly from POC to production while keeping operational rigor with change management.
Detail oriented with a security‑first mindset.
Proven ability to influence technical direction and align cross-functional stakeholders without direct authority.
Skilled at leading technical debates, resolving conflict, and driving decisions in ambiguous, high-stakes environments.
Strong executive communication skills, with the ability to translate complex technical concepts into clear business decisions and risk tradeoffs.

Benefits

Comp & perks

Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development