About This Role
We're hiring an Intelligent Applications Architect to own the technical vision for agentic AI systems. Applications that reason, act, and coordinate across tools to deliver dynamic, responsive, and human experiences spanning web, mobile, and conversational interfaces, including voice. You'll design how these systems actually work: how agents orchestrate tools and APIs, how they retain context and memory across interactions, how large language models and generative AI compose into reliable workflows, and how we keep them observable, evaluable, and safe in production. Working across multiple teams and client engagements, you'll establish the architectural patterns, frameworks, and standards that engineers build on, while staying close enough to the code to prototype hard problems and prove out approaches yourself. This role is ideal for seasoned technologists who have designed and shipped agentic or AI driven systems at scale and want to shape how an entire organization builds them.
What You'll Do
- Own the architecture and technical direction for intelligent applications and agentic platforms across multiple teams and engagements.
- Define the integration patterns and reference architectures for model providers and AI APIs (OpenAI, Azure AI, Anthropic, etc.) across web, mobile, and backend systems.
- Architect voice and conversational interfaces that feel natural and intuitive, from interaction design through to the underlying agent and model layer.
- Define and govern reusable agentic frameworks, component libraries, and platform accelerators that engineering teams build on.
- Serve as the senior technical authority with clients, shaping solution architecture and turning intelligent web and voice ideas into delivery roadmaps.
- Work with data and AI teams on end to end solutions. This is where the agentic architect signal actually lives.
- Design how multiple agents plan, select and use tools, coordinate, and hand off work. Architect retrieval, memory, and context strategies (RAG, embeddings, state management) that keep agents grounded and consistent.
- Define the evaluation, observability, and guardrails that make agents behave reliably and safely in production. This single area is the clearest thing separating an architect from a senior engineer in this space.
- Set standards for model selection, prompt design, and the cost and latency tradeoffs behind them, and make the build versus buy calls across the agentic stack.
- Architect retrieval, memory, and context strategies (RAG, embeddings, state management) that keep agents grounded and consistent.
What You'll Bring
- Must be authorized to work in the United States without sponsorship.
- 10+ years building production software, including several years in a lead or architect role.
- Proven experience designing and shipping production systems built on LLMs and generative AI, including agentic or tool using systems.
- Strong command of API design, security, and data architecture across distributed systems.
- Clear communicator who can influence engineers, executives, and clients, and who enjoys solving hard problems and learning new tech.
- Experience defining technical standards and reference architectures adopted across teams.
- Hands on experience with agent orchestration, tool use, retrieval, and memory.
- Ability to make and defend architectural tradeoffs across reliability, cost, latency, and security.
- Experience building voice agents, conversational interfaces, or AI copilots.
- Cloud experience (Azure, AWS, or GCP).
- Familiarity with vector databases or embedding-based search.
Nice to Have
- Hands on experience with agent frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI, or the model provider agent SDKs.
- Experience with LLMOps and evaluation or observability tooling for AI systems.
- Background in compliance heavy or governance heavy domains where AI reliability and auditability matter.
- Open source contributions, talks, or writing on AI and agentic systems.
- Experience with fine tuning, model customization, or multimodal systems.
What We Offer
- Competitive salary
- Hybrid work arrangement
- Unlimited PTO policy
- Health, dental, and vision insurance
Skills Required
- Authorization to work in the United States without sponsorship
- 10+ years building production software
- Several years in a lead or architect role
- Experience designing and shipping production systems built on LLMs and generative AI, including agentic or tool-using systems
- Strong command of API design, security, and data architecture across distributed systems
- Experience defining technical standards and reference architectures adopted across teams
- Hands-on experience with agent orchestration, tool use, retrieval, and memory
- Ability to make and defend architectural tradeoffs across reliability, cost, latency, and security
- Experience building voice agents, conversational interfaces, or AI copilots
- Cloud experience with Azure, AWS, or GCP
- Familiarity with vector databases or embedding-based search
- Hands-on experience with LangGraph, Semantic Kernel, AutoGen, CrewAI, or model provider agent SDKs
- Experience with LLMOps and evaluation or observability tooling for AI systems
- Background in compliance-heavy or governance-heavy domains
- Open source contributions, talks, or writing on AI and agentic systems
- Experience with fine-tuning, model customization, or multimodal systems







