Front-End Agentic AI Engineer

Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to the exact lines of source code. Rather than replacing engineers, we’re building AI that helps them understand decades of complex software faster, with complete transparency and confidence.

We’re building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. Every response generated by the platform must be explainable, traceable, and trustworthy. The front end is where that trust is earned.

The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements.

When an engineer asks a question about a decades-old codebase, your interface determines whether they trust the answer or close the tab. You’ll own that experience from end to end.

The product has executive sponsorship, committed users, a clearly defined mission, and a customer who knows exactly what success looks like.

Our engineering team is intentionally small. Every engineer has significant ownership, meaningful influence over product direction, and the opportunity to help define how engineers interact with AI.

We don’t simply build AI-powered software-we build software with AI. This is not another chatbot.

Using AI agents, LLMs, parallel workflows, and model-assisted development is simply how we engineer.

What You’ll Do:

• Own the end-to-end front-end experience for an enterprise-scale Agentic AI platform.
• Design intuitive interfaces that transform complex AI reasoning into experiences engineers’ trust.
• Build and maintain conversational interfaces, embedded AI assistants, review workflows, and authoring experiences using React, TypeScript, and modern front-end technologies.
• Develop the rendering pipeline for streaming AI responses, markdown, source citations, code blocks, dependency graphs, workflow visualizations, and technical documentation.
• Build evidence and traceability experiences that allow users to validate AI-generated answers by navigating directly to source code, documentation, and supporting artifacts.
• Design interaction patterns for agentic workflows, including multi-step reasoning, tool execution, progress visualization, human-in-the-loop review, and long-running AI tasks.
• Build responsive real-time user experiences using WebSockets, streaming APIs, and modern state management patterns.
• Partner closely with AI engineers to define how agent output is translated into intuitive user experiences.
• Collaborate with product managers, UX designers, architects, and platform engineers to rapidly prototype, validate, and deliver new capabilities.
• Build scalable component libraries and reusable design systems supporting future platform growth.
• Optimize performance, accessibility, responsiveness, and usability across enterprise environments, including Section 508 compliance.
• Instrument the application with analytics, observability, and client-side monitoring to continuously improve user experience.
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What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

• Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
• Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
• Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
• Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
• Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
• Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

• Bachelor’s degree in Computer Science, Software Engineering, or related discipline (or equivalent professional experience).
• 7+ years of professional front-end software engineering experience building production web applications.
• Expert-level proficiency with React, TypeScript, modern JavaScript, and contemporary front-end architecture.
• Experience building highly interactive, data-rich user interfaces.
• Strong understanding of component architecture, state management, and scalable front-end engineering.
• Experience building real-time user experiences using streaming APIs, WebSockets, or Server-Sent Events.
• Experience consuming complex REST, GraphQL, tRPC, or comparable typed APIs.
• Experience collaborating closely with backend engineers, designers, and product teams in Agile environments.
• Excellent communication skills and the ability to explain technical decisions clearly across engineering and business stakeholders.
• Mindset of a product engineer rather than a feature developer.
• Engineers capable of building software from first principles.
• Passion for usability, interaction design, and developer experience.
• Strong ability to carefully analyze requirements before writing code.
• Preference for ownership over narrowly defined responsibilities.
• Experience operating across the client/server boundary when necessary.
• Expertise using AI coding assistants, parallel agents, and model-driven development workflows.
• Efficiency while maintaining high engineering standards.
• Innate ability to solve difficult engineering problems that don’t have obvious solutions., * Experience in healthcare, regulated industries, or large-scale enterprise modernization programs is a plus.
• Experience building AI-native products, LLM-powered applications, or agentic AI systems.
• Experience designing interfaces for AI assistants, copilots, developer tools, or knowledge platforms.
• Familiarity with Retrieval-Augmented Generation (RAG), vector search, embeddings, or agent orchestration frameworks.
• Experience rendering complex technical content including markdown, syntax highlighting, dependency graphs, diagrams, or code relationships.
• Experience developing products for software engineers or other highly technical users.
• Experience with cloud-native platforms including AWS or Azure.
• Experience building design systems or reusable component libraries.
• Familiarity with accessibility standards including Section 508 and WCAG.
• Experience using AI coding assistants and parallel AI workflows as part of daily software development.

Lead end-to-end front-end development for an enterprise Agentic AI platform. Design interactive, explainable UIs that render streaming LLM outputs, code citations, dependency graphs and authoring workflows. Build real-time experiences with WebSockets/streaming APIs, ensure traceability to source code, collaborate with AI engineers and designers, and drive accessibility, performance, and observability across a FedRAMP-aligned federal deployment. The summary above was generated by AI

At LTS, we support impactful programs that directly improve healthcare services for Veterans nationwide. Our teams work on innovative modernization initiatives that help transform legacy systems into secure, scalable, and mission-focused digital solutions. We value collaboration, integrity, and professional growth while empowering employees to contribute to meaningful federal healthcare missions.