Lead Application & Product Architect, .Net/AI/Audit
Listed on 2026-02-28
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IT/Tech
Systems Engineer, Cybersecurity
As a hands‑on Lead Application & Product Architect
, you will play a critical role in designing and guiding the implementation of applications across the Global Audit portfolio. In this position, you’ll develop detailed product blueprints, data models, integration patterns, and non‑functional requirements (NFRs), ensuring alignment with portfolio standards. You will collaborate closely with product owners and engineering leads, leveraging your ability to code and build quick proofs of concept.
Proficiency in Azure Well‑Architected principles, experience with VS Code and Git Hub Copilot, and the capability to reverse‑engineer .NET solutions to inform pragmatic designs are essential for success in this role.
You will report to the Principal Application & Product Architect and work a hybrid work schedule from our local office (2 days in office, 3 days remote).
Responsibilities:- Own product‑level architecture for audit applications, including diagrams, runtime flows, data models, and integration contracts.
- Select technologies within portfolio standards; document decisions and align with governance.
- Maintain SDD‑compliant documentation (Current/Target/Transition states, security, availability, compliance) in version‑controlled repositories.
- Define and validate NFRs (performance, security, reliability, operability, cost) with measurable criteria.
- Provide technical guidance on APIs, events, caching, resiliency, error handling, and observability.
- Develop POCs and spikes to de‑risk solutions (e.g., retrieval/RAG, workflow integrations, storage lifecycle, performance tuning).
- Reverse‑engineer .NET services; recommend modularization and refactoring strategies.
- Design and ensure backward‑compatible integrations with adjacent systems; enforce contract testing.
- Apply enterprise patterns (API‑first, event‑driven, zero‑trust, IaC) and coach teams on implementation.
- Troubleshoot complex issues; lead root‑cause analysis and implement preventive patterns.
- Publish product architecture documentation and diagrams within 30 days.
- Launch NFR dashboards tracking latency, throughput, availability, error budgets, and security posture.
- Deliver two POCs per quarter with documented ADRs and go/no‑go decisions.
- Meet performance targets: p95 ≤ 250 ms for key interactions; ≤ 500 ms at 3× data scale.
- Achieve reliability goals: service SLO of 99.9% monthly; DR RPO/RTO ≤ 15 minutes.
- 8+ years in software engineering; 3+ years in SaaS or distributed system architecture.
- Hands‑on experience with Azure (or equivalent): AKS/Kubernetes, Key Vault, Blob/ADLS, networking, observability; familiarity with Well‑Architected principles.
- Strong .NET/C# skills, including reverse‑engineering and refactoring legacy code (ASP.NET Core, API design, performance tuning).
- Proficiency with VS Code and Git Hub Copilot for code exploration, test/document generation, and diagramming; disciplined prompt usage.
- Excellent documentation skills: C4, Mermaid, sequence diagrams; ADRs; SDD‑compliant records.
- Proven ability to execute POCs and spikes across storage, search, agent workflows, and APIs; measure/report latency, cost, and robustness.
- Experience applying AI agent design patterns at product level (e.g., Planner–Executor, Manager–Executor, pipeline vs. swarm orchestration).
- Skilled in task decomposition, tool routing, and prompt design with cost/performance guardrails.
- Knowledge of RAG patterns: chunking, citations, provenance, and evidence binding for audit artifacts.
- Expertise in memory/state management: short‑term conversation, long‑term vector/graph, lineage tracking, and immutable evidence stores.
- Familiarity with evaluation and safety loops: self‑critique agents, confidence scoring, HITL gates, policy checks, and audit trails.
- Agent observability: logs, spans, KPIs, trace replay, and incident analysis.
- Event‑driven architecture with Kafka/Confluent, schema registry, and consumer group patterns.
- RAG and retrieval design using Azure AI Search, embeddings, and vector stores.
- Strong security and compliance practices: threat modeling, secure coding, encryption, and key management.
- CI/CD with Azure Dev…
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