Azure AI Architect

About Us:

At Dabster, we specialize in connecting top talent with leading global companies. We are currently seeking a skilled and dedicated
Azure AI Architect
to join our client's team in
Multiple locations, UK (Hybrid).
Our mission is to be the foremost recruitment specialist in securing exceptional talent for a diverse range of global clients.

Who You Will Work With:

Our client is a globally recognized technology company delivering IT services, consulting, and business solutions. They partner with leading organizations worldwide to drive digital transformation, leveraging innovation and deep industry expertise to solve complex business challenges.

Job Summary

As an
Azure AI Architect
, you will lead the end‑to‑end architecture, design, and delivery of enterprise AI solutions built on
Azure AI Foundry
,
Azure OpenAI
,
Azure AI Document Intelligence design
and deploy. You should have hands-on experience in
Azure Data Factory, Azure ML Service, Azure Data bricks, Azure Key Vault, Azure BLOB Storage Account, Azure Log Analytics, Synapse Analytics, Azure DevOps
. You will define the reference architectures and guardrails that enable teams to build secure, scalable, and cost‑efficient AI capabilities—spanning intelligent document processing, generative AI applications, and retrieval‑augmented systems integrated with core enterprise platforms.

You will collaborate closely with business stakeholders, product owners, security and compliance, data engineering, and application teams to translate business outcomes into actionable AI roadmaps and solution designs. You will also guide implementation teams on best practices for prompt engineering, grounding strategies, RAG patterns, observability, MLOps, and Responsible AI—ensuring solutions are robust, compliant, and production‑ready.

This role suits a hands‑on architect who can balance strategic vision with pragmatic delivery, establish engineering standards, and mentor developers while owning architectural decisions and non‑functional requirements (performance, resilience, security, and cost).

Your responsibilities:

• Define target‑state
  Azure AI reference architectures
  leveraging
  Azure AI Foundry
  ,
  Azure OpenAI
  , and
  Azure AI Document Intelligence
  for enterprise use cases (IDP, GenAI copilots, knowledge retrieval).
• Establish standards for
  RAG
  architectures (vectorization, indexing, chunking, grounding, citation policies) using
  Azure Search
  or vector‑enabled data stores.
• Create architectural decision records (ADRs), guardrails, and reusable blueprints for solution teams.
• Lead end‑to‑end solution designs including API contracts, integration patterns (Azure Functions, Logic Apps, Event‑driven), security boundaries, and observability.
• Architect
  document intelligence pipelines
  (classification/extraction/OCR/validation) and integrate with downstream systems (CRM/ERP/ITSM/EDM).
• Define
  non‑functional requirements
  (availability, latency, throughput, cost, DR/RTO‑RPO) and ensure solutions meet them.
• Implement
  identity & access
  (Entra ID), data isolation,
  Key Vault
  secrets, network security (Private Endpoints), and content filtering.
• Embed
  Responsible AI
  practices: safety filters, prompt/content governance, data privacy, red‑teaming guidance, and human‑in‑the‑loop review where needed.
• Ensure regulatory alignment (e.g., GDPR, ISO controls) and collaborate with risk, legal, and security for approvals.
• Define
  MLOps
  processes for versioning, evaluation, promotion, rollback, and monitoring (latency, cost, drift, hallucination rate, safety events).
• Instrument
  observability
  (logging, tracing, metrics) and error budgets; establish SLIs/SLOs for AI services.
• Drive
  FinOps
  discipline—capacity planning, token/cost controls, caching strategies, and model selection/optimization.
• Mentor engineers on prompt engineering, grounding, tool‑use patterns, and quality evaluation frameworks.

Your Profile

Essential skills/knowledge/experience:

• Overall in software/solution architecture with 7
  + years in cloud (Azure)
  and 5
  + years in AI/ML or Azure AI
  solutioning.
• Proven experience leading
  production‑grade
  solutions using
  Azure OpenAI
  ,
  Azure AI Foundry
  ,
  Azure AI Document Intelligence, Azure Data Factory, Azure ML Service, Azure Data bricks, Azure Key Vault, Azure BLOB Storage Account, Azure Log Analytics, Synapse Analytics, Azure DevOps
  .
• You should have hands-on experience in
• Deep knowledge of
  LLMs
  (prompting, system prompts, grounding, evaluation),
  embeddings
  , and
  RAG
  design (index selection, chunking strategies, reranking, citations).
• Strong design of
  secure API
  and event‑driven integration patterns; familiarity with microservices and domain‑driven design concepts.Practical expertise in
  Entra ID
  , RBAC, network isolation (Private Links), secret management,
  data residency
  , and
  Responsible AI
  controls.
• Experience aligning solutions with privacy and compliance requirements (e.g.,
  GDPR
  , ISO 27001 controls) and completing architecture risk assessments.
• Proficiency in
  Python
  and/or
  C#
  for service integration, evaluation tooling, and adapters; solid understanding of REST APIs, JSON, and async patterns.

Desirable skills/knowledge/experience:

• Experience with
  vector databases
  (Cosmos DB with vector search, Redis Enterprise, or Pinecone) and
  semantic ranking
  .
• Knowledge of
  Azure Machine Learning
  for training/evaluation pipelines and model registries.
• Familiarity with
  Power Platform
  (AI Builder, Power Automate) for rapid AI-enabled workflows.
• Exposure to
  multi‑agent
  /tool‑use orchestration, guardrails frameworks, and evaluation harnesses for GenAI.
• Performance engineering (token optimization, caching, partial responses/streaming) and
  cost‑to‑serve
  modeling.

Certifications
:

• Azure AI Engineer Associate, Azure Solutions Architect Expert.

How to Apply

Apply by submitting your resume today, showcasing your relevant experience and passion for the position via LinkedIn Easy Apply or directly to