Principal Architect, AI-Native Developer Experience

BambooHR · Arizona | Remote; Florida | Remote; Georgia | Remote; Idaho | Remote; Nebraska | Remote; North Carolina | Remote; Oklahoma | Remote; Oregon | Remote; South Carolina | Remote; Tennessee | Remote; Texas | Remote; Utah | Remote; Virginia | Remote · Engineering

Posted 2026-11-05

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Please Note: This is a remote position available in the state(s) listed on this job. Additionally, employment with BambooHR is contingent on passing both a background and credit check.

AI at BambooHR

At BambooHR, we believe in leveraging cutting-edge technology to empower people and transform HR. We’re actively integrating AI into our solutions and workflows to enhance efficiency and drive innovation. To that end, we’re looking to our existing team members and future hires to share this forward-thinking mindset: individuals who are curious about AI’s potential, eager to learn and adapt, and ready to explore how intelligent tools can elevate their work along with BambooHR’s impact on setting people free to do great work. Join us in reimagining the future of HR!

Essential Job Duties

Agents now write, review, test, and ship code alongside engineers. As Principal Architect for AI-Native Developer Experience, you will lead the architecture for how BambooHR engineers and agents build software together, from the tools and context agents rely on to the pipelines that validate their work. We are looking for someone who is endlessly curious, stays at the forefront of AI and software technology, and knows when to think a problem through and when to settle it with a working prototype. This is a hands-on role on an award-winning product, with a team that lives our Bamboo Values, at a company that believes you should have a life outside of work.

You will:

Set the direction. Define the technical vision, reference architecture, and incremental roadmap for AI-native development, and document key decisions in ADRs.

Experiment and prove it out. Track emerging models, agents, and developer tools, run time-boxed experiments and proofs of concept, and turn what works into supported patterns while retiring what does not.

Establish and champion agentic engineering practices. Define how engineers work with coding agents (spec-driven development, context engineering, review of agent-generated code), build a shared library of skills, tools, and MCP servers, and evangelize these practices across engineering through demos, playbooks, and communities of practice.

Automate the SDLC with agents. Architect agentic workflows from triage through implementation, review, testing, and remediation, with autonomy levels and human-in-the-loop guardrails set by risk and backed by evals.

Build the knowledge layers. Give agents and engineers accurate, current context through engineering and product knowledge layers: code intelligence, service catalogs, architecture records, domain models, and business rules.

Make domains agent-ready. Define the standard for agent-ready domains (clear boundaries, documented APIs, agent-callable tools, fast tests, ephemeral environments) and help teams close the gaps.

Reimagine CI/CD for the AI era. Redesign the pipeline for the volume of agent-authored changes, with intelligent test selection, merge queues, automated quality and security gates, and progressive delivery.

Rethink the core developer experience. Modernize development environments, onboarding, documentation, and the internal developer portal so they serve engineers and agents alike, and measure developer experience and productivity to guide where we invest.

Govern for trust and cost. Partner with Security, Privacy, and Quality Engineering on agent permissions, sandboxing, and audit trails, and track AI cost and quality so gains hold up.

Lead hands-on and through others. Write production code and reference implementations, partner closely with architects and staff engineers across domains to set direction and land changes, and mentor engineers as they build agentic skills.

What You Need to Get the Job Done

Bachelor’s degree in computer science or a related field, or equivalent experience

At least 10 years of software engineering experience, with at least 7 in software architecture or staff-plus technical leadership

Daily, hands-on use of AI coding agents, and a track record of turning that into practices or tools other engineers adopt

Experience building production LLM systems, including tool calling, agent orchestration, context engineering, RAG, and evals

Deep experience designing CI/CD, build systems, and developer platforms at scale

Strong SaaS architecture fundamentals and fluency in our stack (PHP, React, MySQL)

Working knowledge of the OWASP Top 10 (including for LLM Applications) and supply chain security

A record of influencing architects and senior engineers without direct authority

Sound judgment in ambiguous problem spaces and exceptional communication, including the ability to give and receive direct feedback

What Will Make Us REALLY Love You

You have built agent tooling, MCP servers, or open-source developer tools

You have led AI adoption or productivity change across a large engineering organization

You have built systems handling sensitive data in regulated SaaS (HR, payroll, SOC 2)

What You'll Love About Us

A Great Company Culture that has been recognized by multiple organizations like Inc, and Salt Lake Tribune

Comprehensive health, life, and disability insurance

Generous leave policies that include 4 weeks of vacation, 12 company holidays, parental leave, and volunteer time off so you can enjoy quality of life

401k plans with up to 6% company match

$2000 Paid-Paid Vacation bonus

EAP through Headspace

Check out all our benefits that benefit you

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