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Principal Architect

Job in Melville, Suffolk County, New York, 11775, USA
Listing for: Accommodations Plus International
Full Time position
Listed on 2026-06-22
Job specializations:
  • Software Development
    Software Architect, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 170000 - 190000 USD Yearly USD 170000.00 190000.00 YEAR
Job Description & How to Apply Below

Accommodations Plus International (API) is a technology and services company focused on driving innovation across the travel and transportation industry. We partner with organizations in the airline, cruise, and rail sectors to deliver solutions that improve layover operations, enhance customer experience, and support long-term growth.

Our mission is to make layovers simpler and more efficient for crew members—and we bring that to life through deep industry expertise and a practical, results-driven approach.

Today, API’s platform powers over 18 million crew room nights each year for 100+ airlines and travel operators worldwide. Our Global Reach ensures that airline crews are rested, transported, and connected so global aviation runs on time.

At API, we’re building a culture rooted in succeeding and thriving together. It’s a place where people are encouraged to take ownership, develop their skills, and contribute to work that matters.

If you’re looking to grow your career in a company that values steady progress, real impact, and long-term development, we’d like to meet you!

The opportunity

This is a high-impact architecture role for someone who thinks in systems, speaks in trade-offs, and has genuine hands‑on experience designing for the age of AI.

As Principal Architect, you'll set the technical direction for how we build, integrate, and evolve complex software systems — spanning cloud-native services, data-backed applications, and AI-powered workflows. You'll work across engineering disciplines, bringing coherence to architectural decisions that affect multiple product teams and long-term platform health.

This isn't a governance role. You'll be deeply engaged with engineering teams, shaping how AI agents and LLM-driven workflows are designed, governed, and integrated responsibly — where security and compliance matter as much as velocity.

What you’ll own Enterprise reference architecture.

You define and evolve the architectural blueprint for our core systems — cloud-native services on AWS, Java backends, Angular front-ends, and data layers (Postgres/Oracle). You create the patterns teams reach for because they’re genuinely good, not because they’re mandated.

AI & agent architecture.

You lead the architectural design of AI-enabled systems: LLM integrations, agentic workflows, retrieval-augmented generation (RAG), tool-use patterns, and multi-agent orchestration. You define how AI capabilities are composed into products safely and at scale.

AI Development Lifecycle (AIDLC).

You shape how AI systems are designed, evaluated, monitored, and iterated — from prompt engineering and model selection through to evaluation frameworks, observability, drift detection, and responsible deprecation.

Integration & systems design.

You define integration patterns across services, APIs, event-driven systems, and AI components — ensuring cohesion, resilience, and clear contracts between system boundaries.

Security & compliance by design.

In partnership with App Sec and risk functions, you embed security, PCI/PII compliance, and responsible AI controls into architectural defaults structural, not bolted on.

Technical leadership & mentorship.

You raise the architectural thinking of senior engineers and tech leads through direct engagement, clear documentation, and collaborative design — not top-down control.

Estimation & gate input.

You produce Gate 0 (ROM) and Gate 1 (detailed) architecture estimates for your initiatives, with clearly documented assumptions, risk flags, and dependency inventories that product and portfolio teams can plan from.

What you’ll deliver
  • A coherent, well-documented enterprise architecture that product and platform teams actively use as a reference
  • Architectural patterns for AI agent workflows and LLM integrations that are production‑ready, governed, and reusable
  • An AIDLC framework that guides how AI systems are built, evaluated, and maintained over time
  • Architecture estimates (Gate 0 and Gate
    1) with assumptions logs and risk registers
  • Reduced architectural drift and fewer production issues caused by inconsistent design decisions
  • A culture of architectural thinking that's embedded in engineering teams, not siloed…
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