Staff AI Solutions Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, deploy, and maintain production-level LLM-based solutions and agent workflows.

• Take ownership of the technical strategy and reference architecture for enterprise AI solutions spanning multiple teams and business functions.

• Lead complex, cross-functional AI projects from vague problem identification through to production implementation and measurable business results.

• Define and refine reusable platform capabilities, implementation standards, and governance patterns that facilitate safe and scalable AI adoption beyond individual teams.

• Review AI agents and solutions developed by citizen developers to provide optimization recommendations, ensure adherence to guidelines, and assess value.

• Shape the company’s roadmap and investment choices through technical leadership and analysis of business value.

• Facilitate technical discussions, align stakeholders on trade-offs, and remove obstacles for multi-team execution on strategically significant AI projects.

• Implement, review, and validate code produced by models; write production-quality code and conduct code reviews to guarantee accuracy and security.

• Develop robust integrations and connectors (MCP, REST/GraphQL APIs, webhooks, SDKs, CLIs) between AI tools and enterprise SaaS applications (e.g., Okta, Google Workspace, Slack, Jira, Confluence, Jamf).

• Manage the end-to-end deployment and lifecycle of AI services: CI/CD pipelines, Infrastructure as Code modules (Terraform), cloud deployment (GCP/AWS), monitoring, and incident/runbook procedures.

• Establish and manage model evaluation, monitoring, and governance processes: metrics for accuracy and safety, hallucination detection, drift monitoring, telemetry, alerting, and human-in-the-loop controls.

• Lead evaluations and proof of concepts for commercial and open-source LLM/agent platforms; produce comparative assessments on performance, risk, and total cost of ownership to guide adoption.

• Collaborate with Cybersecurity and Compliance teams to design data handling practices that ensure safety for PHI (sanitization, tokenization, least-privilege access, audit logging) and confirm that AI solutions comply with relevant regulations and policies.

• Create and uphold architecture diagrams, API documentation, runbooks, support materials, and onboarding resources to ensure solutions are maintainable and verifiable.

• Mentor engineers and shape architectural standards for AI/LLM adoption across the Digital Workplace; contribute reusable libraries and Infrastructure as Code modules to expedite future developments.

• Automate operational tasks (such as provisioning, onboarding, and common workflows) through the use of agents and workflow tools to minimize manual efforts.

• Collaborate with Technology Services leadership to establish AI spend management solutions and track value.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

• Over 8 years of professional experience in software engineering or systems integration.

• Hands-on experience managing the complete lifecycle of LLMs and agents.

• Proficient in evaluating model performance, mitigating hallucinations and biases, and implementing human-in-the-loop controls.

• Ability to define reference architectures and reusable patterns for AI services utilized by various teams.

• Experience balancing architectural trade-offs related to reliability, latency, cost, security, and maintainability in production systems.

• Proven track record in establishing engineering standards, guardrails, and paved-road patterns for AI development and deployment.

• Experience in optimizing model/runtime costs, implementing usage controls, and measuring value.

• Strong programming skills in Python and/or TypeScript/JavaScript, with a focus on production software engineering principles (code reviews, testing, CI/CD).

• Experience designing and building API integrations (REST/GraphQL), webhooks, and custom connectors to SaaS platforms.

• Familiarity with Infrastructure as Code (Terraform) and deploying services on cloud platforms (GCP/AWS).

• Understanding of CI/CD tools and best practices for observability (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 highly preferred.

• Excellent communicator and collaborator capable of converting ambiguous business requirements into technical solutions and influencing cross-functional stakeholders.

• Proactive mindset: ability to transition quickly from proof of concept to production while maintaining operational rigor with change management.

• Detail-oriented with a security-first approach.

• Demonstrated ability to influence technical direction and align cross-functional stakeholders without direct authority.

• Skilled in leading technical discussions, resolving conflicts, and making decisions in high-pressure, ambiguous situations.

• Strong executive communication skills, able to translate complex technical concepts into clear business decisions and risk trade-offs.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development