Job description

As a Principal Agentic Software Engineer, Quality Systems , you are a hands-on, product-minded, customer-focused full-stack engineer who sets technical direction across multiple products and platforms and personally builds the primitives other teams depend on. This is a builder's seat with a quality center of gravity. You direct AI coding agents through real, multi-step work, and you own the harder half of that equation: knowing when the output is right. As we ship faster with agents, the engineers who can tell correct code from plausible-looking code become the ones everything else rests on. You decide what becomes shared infrastructure, make the build-vs-buy calls that shape our roadmap, and build the evaluation and test systems that let the rest of engineering move quickly without breaking trust. Your work reaches millions of people. We build the travel and rewards platforms behind major banks, membership organizations, and travel brands, where members book real trips with real money and points, so trust is the product. Operating with broad autonomy and cross-organizational accountability, you will lead the one-way-door decisions in your areas, balance short-term partner requests against long-term member trust, and set the operating rhythms, launch gates, and quality standards that let dependent teams move faster while protecting it. What You'll Own • Technical direction: Set direction across multiple products and platforms, including AI infrastructure, data platforms, and shared primitives, and personally build the components that increase leverage for teams beyond your own. • Agentic engineering practice: Co-define our prompt libraries, MCP server patterns, quality gates for AI-generated code, and human-agent collaboration patterns, then get them adopted. • The quality bar for agent output: Define how AI-generated code gets reviewed and validated for correctness, security, performance, and maintainability, and build the tooling that makes that judgment repeatable rather than heroic. • Test and evaluation infrastructure: Architect the automated testing, regression, and AI evaluation systems that other teams build on, including eval frameworks, guardrail dashboards, and the harnesses that catch silent failures a green test suite would miss. • MCP integrations: Architect Model Context Protocol integrations that give AI agents secure, governed access to internal APIs, data sources, and platform services across teams. • Agentic quality workflows: Define patterns and platforms that automate testing, documentation, code-review triage, and deployment checks at scale. • Standards and simplification: Drive build-vs-buy decisions and convergence on strategic standards that reduce complexity rather than add to it. • Operating rhythms: Institutionalize prioritization mechanisms, AI launch checklists, and SLOs that raise quality and speed for dependent teams. • High-stakes decisions: Lead one-way-door decisions in your areas, minimize the chance of failure, and hold contingency plans for failure scenarios. • Data and evaluation culture: Standardize canonical metrics, minimum sample sizes, and release criteria, and hold teams to them before anything scales. • Responsible AI: Co-define responsible-AI guardrails and review processes so high-risk use cases get scrutiny and post-incident learnings feed back into design standards. • Modernization: Turn legacy systems into scalable, cloud-native, agent-ready services through clear migration paths and architectural patterns. • Trust and safety: Safeguard members' sensitive data by defining security patterns and partnering with our Risk, Security, and Compliance teams. • People and norms: Mentor staff-level engineers and shape technical-leadership norms across individual contributors, so strong solutions emerge from teams and not from you alone. What You'll Bring You do not need every item below. We are excited by candidates with real strength across several of these areas. • A recent, hands-on track record. You have personally built and shipped working software in the last year or two, not only led teams who did. • 8 to 12 years of full-stack development and architecture experience building web applications and services, including technical leadership beyond a single team. • A bachelor's degree in Computer Science, Computer Engineering, or equivalent experience. • Advanced, hands-on use of AI coding agents such as Claude Code, Cursor, or GitHub Copilot, including directing them through larger multi-step work, with a track record of building practices that others adopt. • Real depth in software quality: test strategy and automation frameworks, CI-gated quality checks, and the judgment to know what is worth testing and what is not. You have owned quality as an engineering problem, not a process one. • Strong proficiency in two or more of TypeScript/JavaScript, Python, and C#/.NET, plus modern frontend frameworks such as React, Next.js, Vue, or Angular. • Deep experience with RESTful API design, distributed systems, and microservices at scale, and cloud-native delivery on AWS, Azure, or GCP including multi-region or hybrid deployments. • Hands-on depth with the Model Context Protocol, prompt engineering for code, and AI building blocks such as Azure AI Foundry, RAG, LangChain, or graph-based data technologies like GraphRAG and GraphDB. • Production experience with real-time streaming and distributed messaging such as Redis, Kafka, or RabbitMQ, plus containerization and orchestration with Docker and Kubernetes, advanced CI/CD, infrastructure-as-code, and modern DevOps or SRE practices. • A record of mentoring senior engineers and raising the bar through frameworks and standards, and of explaining complex AI and architectural ideas simply to executives and non-technical partners. Benefits & Perks • Unlimited PTO • Exclusive employee travel rates • Travel discounts through arrivia programs • Medical, dental, and vision insurance • 401(k) with company participation Who We Are arrivia is the leading provider of travel loyalty, membership, and cruise solutions, powering travel experiences for millions of members through some of the world's most recognized brands, including T-Mobile, Marriott Vacations Worldwide, Hilton Grand Vacations, American Express, Alaska Airlines, Singapore Airlines, and more. We're combining travel, technology, and innovation to build the future of loyalty. Through continued investment in AI, automation, and next-generation travel solutions, arrivia is transforming how people discover, book, and experience travel around the world.

Requirements

Must-haves

What You'll Own
Agentic engineering practice: Co-define our prompt libraries, MCP server patterns, quality gates for AI-generated code, and human-agent collaboration patterns, then get them adopted.
MCP integrations: Architect Model Context Protocol integrations that give AI agents secure, governed access to internal APIs, data sources, and platform services across teams.
Agentic quality workflows: Define patterns and platforms that automate testing, documentation, code-review triage, and deployment checks at scale.
Standards and simplification: Drive build-vs-buy decisions and convergence on strategic standards that reduce complexity rather than add to it.
Operating rhythms: Institutionalize prioritization mechanisms, AI launch checklists, and SLOs that raise quality and speed for dependent teams.
High-stakes decisions: Lead one-way-door decisions in your areas, minimize the chance of failure, and hold contingency plans for failure scenarios.
Data and evaluation culture: Standardize canonical metrics, minimum sample sizes, and release criteria, and hold teams to them before anything scales.
Responsible AI: Co-define responsible-AI guardrails and review processes so high-risk use cases get scrutiny and post-incident learnings feed back into design standards.
Modernization: Turn legacy systems into scalable, cloud-native, agent-ready services through clear migration paths and architectural patterns.
Trust and safety: Safeguard members' sensitive data by defining security patterns and partnering with our Risk, Security, and Compliance teams.
People and norms: Mentor staff-level engineers and shape technical-leadership norms across individual contributors, so strong solutions emerge from teams and not from you alone.
You do not need every item below. We are excited by candidates with real strength across several of these areas.
A recent, hands-on track record. You have personally built and shipped working software in the last year or two, not only led teams who did.
8 to 12 years of full-stack development and architecture experience building web applications and services, including technical leadership beyond a single team.
A bachelor's degree in Computer Science, Computer Engineering, or equivalent experience.
Advanced, hands-on use of AI coding agents such as Claude Code, Cursor, or GitHub Copilot, including directing them through larger multi-step work, with a track record of building practices that others adopt.
Strong proficiency in two or more of TypeScript/JavaScript, Python, and C#/.NET, plus modern frontend frameworks such as React, Next.js, Vue, or Angular.
Deep experience with RESTful API design, distributed systems, and microservices at scale, and cloud-native delivery on AWS, Azure, or GCP including multi-region or hybrid deployments.
Hands-on depth with the Model Context Protocol, prompt engineering for code, and AI building blocks such as Azure AI Foundry, RAG, LangChain, or graph-based data technologies like GraphRAG and GraphDB.
A record of mentoring senior engineers and raising the bar through frameworks and standards, and of explaining complex AI and architectural ideas simply to executives and non-technical partners.

Nice-to-haves

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Keywords to mirror

airesttypescriptjavascriptpythonreactnext.jsvueangularapiawsazuregcpdockerkubernetesci/cd

Platform: ukg
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto