Staff Full Stack AI Engineer

Accountabilities

• Work directly with client teams to discover, scope, architect, and deliver full-stack applications, taking ownership from ambiguous requirements through production.
• Design, develop, and deploy scalable web applications using technologies such as React, Next.js, TypeScript, modern back-end frameworks, and cloud platforms.
• Identify, prototype, and productionize AI capabilities, including LLM integrations, retrieval-augmented generation (RAG), agentic workflows, tool/function calling, and intelligent automation.
• Build AI solutions with appropriate evaluation frameworks, guardrails, security considerations, and awareness of model cost and latency trade-offs.
• Use AI-assisted development tools to increase engineering velocity while maintaining strong standards for quality, reliability, and maintainability.
• Implement infrastructure-as-code and automated deployment pipelines to create scalable, observable, and dependable solutions.
• Develop automated testing strategies, including unit, component, integration, and AI evaluation testing, to ensure robust production outcomes.
• Conduct thorough code reviews, establish engineering best practices, and maintain high technical standards in fast-moving, client-facing environments.
• Provide technical leadership and mentorship, helping engineers and clients strengthen their full-stack and AI capabilities.
• Manage delivery expectations with stakeholders, balancing scope, quality, timelines, technical trade-offs, and engagement constraints.
• Shape technical direction across teams and engagements, documenting architectural decisions and the trade-offs behind them.
• Stay current with rapidly evolving AI and web technologies and develop informed perspectives on where emerging tools and models can create meaningful business value.

Requirements

• 7+ years of experience working on substantial software development projects, with strong expertise in React and modern front-end engineering.
• Advanced TypeScript skills and strong knowledge of modern React concepts, including component lifecycles, hooks, concurrent features, Server Components, and Next.js App Router patterns.
• Experience with state-management approaches such as Redux, Context, and RTK Query, with an understanding of when to apply each.
• Strong testing experience using tools such as Jest, Vitest, React Testing Library, Cypress, or comparable frameworks.
• 5+ years of experience developing and integrating REST APIs and back-end services using technologies such as Node.js, .NET, Ruby on Rails, Go, or similar.
• Hands-on experience with a major cloud platform such as AWS, Azure, or GCP, together with infrastructure-as-code practices.
• Demonstrated ability to architect complex software systems, make sound design decisions, and clearly document technical trade-offs.
• 2+ years of practical experience building modern AI capabilities that have been delivered into real products or client engagements.
• Experience integrating LLMs through major provider APIs such as OpenAI, Anthropic, or equivalent platforms.
• Working knowledge of RAG, vector databases, embeddings, prompt engineering, agentic architectures, orchestration frameworks, and tool/function calling, including protocols such as MCP.
• Understanding of AI evaluation, guardrails, safety, observability, and the cost-versus-latency considerations involved in production AI deployments.
• Strong proficiency with AI-assisted development tooling and an ability to use these tools as a force multiplier for engineering delivery.
• Proven consulting and problem-solving skills, with the ability to ramp quickly on unfamiliar technologies, codebases, business domains, and client organizations.
• At least 3 years of experience leading engineering teams, mentoring engineers, and planning and strategizing delivery.
• Strong client-facing communication skills and the ability to translate business requirements into practical technical solutions.
• Ability to understand how technical decisions affect engagement scope, timelines, and commercial outcomes.
• Comfortable operating in ambiguous, fast-moving environments while collaborating effectively with distributed and multidisciplinary teams.
• Strong curiosity, willingness to learn, and commitment to delivering high-quality products and features.
• Nice-to-have experience includes taking AI features from prototype to production, managing scaled front-end architectures, CI/CD and DevOps, authentication, application security, AI observability, or model customization such as fine-tuning and distillation.

Benefits

• Competitive compensation with location- and experience-dependent salary ranges.
• For Colorado-based positions, an estimated salary range of $145,000–$175,000 USD annually.
• For New York City-based positions, an estimated salary range of $160,000–$190,000 USD annually.
• Eligibility for additional compensation and benefits according to role and location.
• Flexible PTO and work-from-home policies.
• 401(k) matching.
• Health, dental, and vision benefits starting on day one.
• Continuing education and professional development opportunities.
• Health and wellness programs.
• Company lunches, outings, and workplace perks.
• Additional location-specific benefits and perks.
• Remote work environment with opportunities to collaborate with diverse, distributed teams.
• Travel for team and client meetings, typically up to 15%.