Staff Full-Stack AI Engineer

Lead the design, development, testing, deployment, observability, and production support of complete applications spanning user interfaces, APIs, backend services, integrations, data access, cloud services, and AI-enabled components.

Build both GenAI functionality and conventional application functionality based on the needs of the initiative; do not limit ownership to the AI service layer.

Translate ambiguous business and healthcare workflow requirements into clear technical strategies, designs, incremental releases, and measurable production outcomes.

Design secure, maintainable REST APIs, event-driven services, system integrations, and responsive web experiences that integrate naturally with existing AssistRx platforms.

Resolve cross-team dependencies and take proven pilots through production hardening and scale across products and clients.

Set standards for CI/CD, source control, containerization, and infrastructure-as-code practices for AI workloads

Serve as the escalation point for complex production issues and client-reported defects in AI-enabled features, leading root cause analysis and continuous improvement of deployed AI services

Evaluate architectural alternatives and select languages, frameworks, data stores, integration patterns, and cloud services based on business fit, scalability, security, maintainability, cost, and delivery speed.

Translate ambiguous business and clinical workflow requirements into technical strategies, designs, and production releases, taking proven pilots to scale across products and clients

Work productively across multiple programming languages and architectural styles rather than defaulting to a single preferred stack.

Author and review design documentation covering system boundaries, interfaces, data flows, security controls, failure modes, observability, evaluation, and fallback behavior.

Identify technical debt and platform gaps, then lead pragmatic investments that improve delivery across multiple teams.

Create reusable components, reference implementations, and engineering standards that accelerate both AI-enabled and conventional application development.

Design and implement production LLM applications using retrieval-augmented generation, structured outputs, prompt design, function and tool calling, and agent-based orchestration.

Develop interactive AI products such as chat, conversational interfaces, voice experiences, assistants, and agentic workflows that are integrated into complete user journeys.

Design clear system boundaries, memory and state management, routing, human review checkpoints, fallback paths, and deterministic controls for high-impact workflows.

Select, tune, and evaluate models against defined targets for accuracy, groundedness, hallucination rate, task completion, latency, and cost

Design agentic workflows with task decomposition, tool and function calling, memory and state management, routing, clear boundaries, human review checkpoints, and fallback paths for high-impact decisions such as benefits verification and prior authorization

Establish practical evaluation, regression testing, monitoring, cost management, content safety, and responsible AI practices.

Evaluate commercial models, AI platforms, and vendor tools and make evidence-based build-versus-buy recommendations.

Build solutions that satisfy healthcare privacy, data security, and regulatory requirements, including HIPAA and HITRUST

Partner with Security and Compliance to address AI-specific risks such as prompt injection, data leakage, and insecure output handling, and to confirm vendor agreements (including Business Associate Agreements) are in place before PHI is processed

Define guardrails, content filtering, human oversight, and audit trails appropriate to the risk profile of each use case

Document model design, data sources, intended use, and known limitations to support internal AI governance, audits, and client due diligence

Provide hands-on technical leadership for complex initiatives and raise the engineering bar through code, architecture reviews, troubleshooting, and production readiness reviews.

Mentor engineers across frontend, backend, cloud, integration, and AI development; share patterns that make teams more effective.

Partner with Product Management and business stakeholders to prioritize work by business value, feasibility, risk, and total cost of ownership.

Communicate technical decisions and trade-offs clearly to engineering, product, security, compliance, and business stakeholders.

Participate in day-to-day agile team activities, including sprint planning, daily standups, sprint reviews, and retrospectives

Apply and help improve AI-assisted and agentic development practices within the engineering organization, including specification-driven workflows and agentic coding tools, and share what works with engineering peers

Conduct regular self-guided study to stay current in a fast-moving AI landscape, and bring relevant new techniques and tooling to the team’s attention

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.

7+ years of professional software engineering experience building and operating production systems, with meaningful experience delivering AI or machine learning capabilities in production.

Strong full-stack engineering experience, including modern web application development, REST APIs, backend services, data access, integrations, automated testing, and production operations.

Production experience with at least two general-purpose application development languages, such as C#, Java, Python, TypeScript/JavaScript, Go, or comparable languages.

Hands-on experience with a modern frontend framework such as React, Angular, Vue, or a comparable framework.

Strong experience with cloud architecture, distributed systems, containers, CI/CD, infrastructure as code, observability, application security, and performance troubleshooting.

Hands-on experience delivering LLM or GenAI capabilities within end-user applications, including RAG, tool/function calling, evaluation, guardrails, and monitoring.

Demonstrated ability to learn unfamiliar technologies, compare architectural options, and choose the right implementation approach for the problem.

Strong written and verbal communication, technical judgment, and experience mentoring engineers and leading cross-team technical work.

Technical Depth

Analytical Rigor & Problem Solving

Experimentation & Measurable Outcomes

Accuracy & Quality

Sound Judgment & Risk Awareness

Ownership & Accountability

Pragmatism & Bias for Delivery

Communication

Collaboration & Influence

Technical Leadership & Mentorship

Curiosity & Learning Agility

Adaptability

Initiative & Innovation

Ethics & Integrity

PHYSICAL DEMANDS AND WORK ENVIRONMENT:

Occasionally required to stand.

Occasionally required to walk.

Frequently required to sit.

Continually required to utilize hand and finger dexterity.

Continually required to talk or hear.

Specific vision abilities required by this job include close vision and the ability to adjust focus.