Application Architect - Enterprise & AI

Accommodations Plus International•Melville, NY

5h•$120,000 - $130,000•Onsite

About The Position

This is a delivery-focused architecture role for someone who loves turning complex business problems into working technical solutions. As an Application Architect, you’ll be the technical lead on product and platform initiatives — taking requirements from product and engineering and designing the systems needed to deliver them. You’ll work closely with delivery teams, product owners, and engineering leads, making the architecture decisions that keep initiatives on track and technically sound. You’ll be embedded in delivery — shaping how AI-enabled features, integrations, and services are designed and built responsibly, with security and compliance embedded from the start.

Requirements

5–10 years in software engineering, with meaningful experience in solution or technical architecture roles on multi-team delivery programs
Solid cloud architecture experience on AWS — services, networking, data, and security patterns in a delivery context
Hands-on experience designing and integrating AI-powered features — including LLMs, RAG patterns, and agentic workflows
Strong integration design skills — APIs, event-driven systems, service boundaries, and resilience patterns
Good working knowledge of backend services (Java ecosystem preferred), data systems, and front-end integration points
Experience in regulated environments (PCI/PII) and comfort embedding compliance requirements into design
Able to produce clear architecture artefacts: component diagrams, sequence diagrams, ADRs, and integration specs
Makes things clear and builds trust quickly with delivery teams.
Writes well — design docs are readable, assumptions are explicit, and trade-offs are explained.
Excited about AI’s potential in product but grounded about what that means in practice.

Nice To Haves

You’ll be embedded in delivery — shaping how AI-enabled features, integrations, and services are designed and built responsibly, with security and compliance embedded from the start.
You translate product and business requirements into clear, well-reasoned technical designs — component diagrams, integration specs, data models, and sequence flows that engineering teams can build from. You work within enterprise reference architecture, applying the right patterns for the problem at hand.
You design AI-enabled features and workflows within your initiatives: LLM integrations, agentic flows, retrieval-augmented generation (RAG), and tool-use patterns. You make these capabilities concrete, buildable, and production-ready — informed by the architectural standards set at enterprise level.
You define how your solution integrates with surrounding services, APIs, event-driven systems, and external platforms — with clear contracts, resilience patterns, and well-understood boundaries.
In partnership with AppSec and risk functions, you ensure security controls, PCI/PII requirements, and responsible AI practices are embedded in solution design — not retrofitted during delivery.
You guide and review engineering work throughout the build — attending design sessions, reviewing pull requests where it matters, and helping teams navigate technical decisions without creating bottlenecks.
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.
Well-documented solution architectures for each initiative — clear enough that engineering teams can build without constant clarification
Integration designs with explicit API contracts, event schemas, and data ownership boundaries
Architecture estimates (Gate 0 and Gate 1) with assumptions logs and risk registers
AI feature designs that are production-ready, governed, and aligned with enterprise AI patterns
Fewer late-stage surprises caused by integration gaps, compliance oversights, or unresolved NFRs
You’ll be designing across a modern, cloud-native stack. You don’t need to be an expert in all of it, but you should be able to navigate it confidently and make good architectural decisions within AWS, Java, Angular, Oracle, PostgreSQL, Amazon Kiro, Kafka, SQS, GitHub etc
AI tooling is evolving quickly. We expect our architects to stay close to that evolution — evaluating new capabilities critically and integrating them where they genuinely improve outcomes, not just for novelty.
Architecture here is a delivery function, not an ivory tower. We work in agile delivery teams, and solution architects are embedded participants — not external reviewers who parachute in at the start and disappear until go-live.
You’ll attend sprint ceremonies, backlog refinement sessions, and design reviews as a first-class team member. Architecture decisions are made iteratively — you’ll produce just enough design upfront to unblock the team, then evolve it as delivery progresses and complexity becomes clearer.
Significant architectural decisions are documented in Architecture Decision Records (ADRs) and reviewed by the Principal Architect. You’ll lead the preparation and presentation of your solutions, with the Principal Architect providing governance and pattern alignment rather than sign-off on every detail.
Most initiatives touch shared platforms, APIs, or data services owned by other teams. You’ll be expected to negotiate integration contracts, resolve boundary disputes, and align across teams without needing escalation for every decision.
We write things down. Architecture artefacts — diagrams, ADRs, integration specs, assumptions logs — are first-class outputs of your role, not afterthoughts. Good documentation reduces re-work, enables team autonomy, and is a mark of craft.
Get across the enterprise reference architecture, approved patterns, and existing system landscape. Meet your product and engineering counterparts. Begin designing the solution for your first assigned initiative.
Deliver your first application architecture. Run design reviews with delivery teams and iterate based on feedback. Produce a Gate 1 estimate ready for build commitment.
Embed into delivery rhythm — design sessions, sprint reviews, and integration checkpoints. Begin contributing architectural observations back to the Principal Architect to inform pattern refinement.
Mentorship from the Principal Architect. You’ll have regular 1:1 time with the Principal Architect — not just for design reviews, but for deliberate coaching on architectural breadth, strategic thinking, and stakeholder influence. The Principal Architect is invested in developing application architects who can grow into senior and principal roles over time.
Architecture community of practice. We run a fortnightly architecture community that brings application architects, tech leads, and the Principal Architect together to discuss patterns, review emerging technology, and share lessons from delivery. This is a learning environment, not a governance forum.
Career progression. For strong performers, the natural path from this role is a Principal Architect, with time and breadth, Enterprise Architect. We’re explicit about what that progression requires and actively support the people who are working toward it.
External development. We support ongoing professional development through cloud certifications (AWS Solutions Architect Professional), architecture frameworks (TOGAF), and attendance at relevant industry events and conferences.
You’ll work closely with product owners, delivery leads, engineering teams, and InfoSec on a day-to-day basis. You’ll engage with the Principal Architect on standards alignment, pattern exceptions, and cross-initiative design issues. You’re the technical voice on solution decisions — with the credibility to challenge scope, surface risk, and unblock delivery.

Responsibilities

Solution design for your initiatives. You translate product and business requirements into clear, well-reasoned technical designs — component diagrams, integration specs, data models, and sequence flows that engineering teams can build from. You work within enterprise reference architecture, applying the right patterns for the problem at hand.
AI & agent implementation design. You design AI-enabled features and workflows within your initiatives: LLM integrations, agentic flows, retrieval-augmented generation (RAG), and tool-use patterns. You make these capabilities concrete, buildable, and production-ready — informed by the architectural standards set at enterprise level.
Integration & API design. You define how your solution integrates with surrounding services, APIs, event-driven systems, and external platforms — with clear contracts, resilience patterns, and well-understood boundaries.
Security & compliance by design. In partnership with AppSec and risk functions, you ensure security controls, PCI/PII requirements, and responsible AI practices are embedded in solution design — not retrofitted during delivery.
Technical governance within delivery. You guide and review engineering work throughout the build — attending design sessions, reviewing pull requests where it matters, and helping teams navigate technical decisions without creating bottlenecks.
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.