Senior AI Architect

Senior AI Architect · Contract, Remote | Azure Preferred | AI Systems and LLM Applications · Company Description · Alyra Technology builds AI-enabled SaaS and automation products that help SMBs to enterprise teams move faster, operate leaner, and grow revenue without adding headc ...

Descrição do trabalho

Senior AI Architect

Contract, Remote | Azure Preferred | AI Systems and LLM Applications

Company Description

Alyra Technology builds AI-enabled SaaS and automation products that help SMBs to enterprise teams move faster, operate leaner, and grow revenue without adding headcount. We create new software in categories that have been underserved or stuck in legacy tooling, especially in document-heavy, regulated environments where accuracy and auditability are non-negotiable. We build on modern Azure architecture and applied AI to deliver systems that are explainable, traceable, and production-ready.

We move fast, ship continuously, and measure impact in days and weeks, not quarters. If you want high ownership, hard problems, and the satisfaction of building products that do not exist yet, you'll fit here.

Role Description

We are hiring a Senior AI Architect for an hourly, advisory engagement. Your job is to set the technical direction that makes our teams win: architecture framing, guardrails, design validation, and rapid decision-making across multiple client and product projects. You will work across AI application architecture and Azure cloud foundations to ensure systems are secure, observable, reliable, and cost-aware.

You will help us build production-grade AI systems, not demos. That includes setting standards for traceability, auditability, and cost-aware performance, and ensuring teams are accountable to measurable outcomes.

You must be able to ramp quickly across new domains and projects, define the architecture, and set the team up with a clear build plan, risks, and guardrails.

Engagement Model

• Contract, remote, hourly
• Bench role, pulled in as projects launch
• Typical cadence: One weekly sync plus asynchronous reviews
• Typical involvement: 5 to 15 hours per week, with the ability to flex higher during active build phases when needed
• Operating style: set direction, validate, step out
• Not responsible for day-to-day delivery management

What You Will Do

• Define target architecture and technical direction for selected initiatives
• Produce and review architecture artifacts: diagrams, ADRs, RFCs, decision logs
• Run design reviews and provide actionable feedback across systems, APIs, data, security, and AI components
• Define service boundaries, contracts, integration patterns, and API strategy
• Identify scalability, reliability, security, and cost risks early and propose mitigations
• Define standards and reference architectures that teams can execute repeatedly
• Ensure production readiness: IaC, CI/CD, observability, incident resilience, and cost controls
• Drive crisp trade-offs and go/no-go calls without over-engineering
• Lead light technical discovery sessions and translate business requirements into architecture direction, acceptance criteria, and non-functional requirements
• Collaborate closely with engineers to raise architecture quality through patterns, reviews, and practical guidance
• Define SaaS platform standards where relevant: multi-tenant boundaries, RBAC, audit logs, data retention, versioning, and migrations
• Establish measurable success criteria for AI systems (quality, traceability, latency, and cost) and reinforce them through reviews and standards

AI Architecture Expectations (Required)

• LLM application patterns: RAG, prompt orchestration, tool/function calling, agents when justified, fine-tuning models, multi-agent systems
• Evaluation discipline: guardrails, measurable quality metrics, golden sets, regression tests
• Retrieval systems: hybrid retrieval patterns, reranking awareness, vector databases (pgvector, Pinecone, Weaviate, or equivalents)
• Production concerns: latency, failure handling, caching/batching, usage-based cost visibility
• Responsible AI mindset appropriate for production systems

Azure Cloud Expectations (Strongly Preferred)

• Deep, hands-on Microsoft Azure experience
• Architecture across networking, identity, security, and data platforms
• Security-by-design: least-privilege RBAC, managed identities, Key Vault, private networking
• IaC: Terraform and/or Bicep with reusable modules and environment parity
• CI/CD: GitHub Actions and/or Azure DevOps
• Observability: Azure Monitor, Application Insights, Log Analytics, alerting, tracing concepts
• Event-driven patterns: Service Bus and/or Event Grid
• Edge and API protection: Front Door, WAF, API Management, private endpoints

Must Have Requirements

• 10+ years in software engineering with proven architecture leadership
• Built and shipped production systems at scale
• Strong distributed systems fundamentals: consistency, fault tolerance, scalability
• Strong trade-off judgment: build vs buy, cost vs performance, monolith vs services
• Strong technical writing: clear ADRs, concise docs, simple diagrams
• Clear communicator, low-ego collaborator, decisive in advisory mode

Strongly Preferred

• Regulated domain experience: insurance, legal, finance, healthcare
• Document-heavy workflows: PDFs, contracts, forms, claims
• SaaS platform architecture experience: multi-tenant design, RBAC, audit logging, tenancy isolation
• Compliance readiness experience (SOC2 or similar), data residency, and audit trail patterns

Success Looks Like

• Teams ship faster with fewer rewrites because decisions are clear and documented
• Risks are surfaced early with concrete mitigations
• Production behavior is reliable and observable, and costs are predictable
• Architecture patterns become reusable across projects

Compensation

Compensation will be discussed and finalized based on experience, scope, and performance expectations. Equity or long-term incentive opportunities may be available for exceptional fits and can be discussed later in the process.