AI Architect

About The Role (your Why) We are looking for an AI Architect to define and drive the technical vision for our AI‑powered solutions. In this role, you will be the key technical authority responsible for designing end‑to‑end AI architectures that are scalable, secure, and production‑ready. You will bridge the gap between business strategy and technical execution — translating complex requirements into robust architectural blueprints that leverage modern cloud platforms, large language models, and agentic AI patterns. You will guide engineering teams, evaluate and select technologies, establish architectural standards, and ensure our AI solutions are built on solid foundations. You will join our Digital Engineering leadership team, working across multiple workstreams to shape the future of AI‑driven solutions at Datacom. What You’ll Do You will own the end‑to‑end technical architecture for AI‑powered solutions across multiple customer engagements. You will evaluate, select, and standardise AI technologies, frameworks, and platforms for the organisation, create reference architectures, design patterns, and best practices for AI solution delivery, lead architectural reviews, and provide technical governance across delivery teams. You will collaborate with product owners, data scientists, and engineering leads to translate business requirements into scalable technical designs, design data architectures that support AI workloads, establish engineering standards for AI quality, testing, security, and observability, guide build‑vs‑buy decisions, manage vendor and partner technology relationships, mentor and uplift engineering teams, stay current with the AI landscape, and present architectural visions and technical strategies to senior stakeholders and customers. What You’ll Bring AI Expertise in agentic AI and multi‑agent orchestration (tools, planning, reflection, chain‑of‑thought) Build AI evaluation frameworks with metrics, benchmarks, and QA for non‑deterministic systems Proficiency in prompt engineering, management, and security (injection prevention, guardrails) Ensure reliable model serving, GPU optimisation, and cost‑aware inference Solution Architecture Design end‑to‑end solutions across frontend, backend, data, and AI layers Create architectural decision records, reference architectures, and technical design documents Master distributed systems, event‑driven architectures, and microservices Develop AI data architecture (modeling, pipelines, governance) Design API patterns (REST, GraphQL, gRPC) for robust AI service integration Address security with threat modelling, responsible AI, data privacy, and compliance Cloud Platforms & Infra Maintain expert‑level Azure/AWS/GCP cloud architectures Leverage AI managed services (Bedrock, SageMaker, Vertex AI, Azure OpenAI) Use serverless and container patterns (ECS/EKS, Cloud Run, Lambda) Build vector/search infrastructure (Pinecone, Weaviate, pgvector, OpenSearch) Apply Infrastructure as Code (Terraform, CDK, Pulumi) and GitOps Focus on AI FinOps and cost optimisation Programming & Technical Depth Excel in Python for prototyping, review, and critical decisions Use TypeScript/JavaScript for full‑stack design Employ AI frameworks (Semantic Kernel, AgentCore, etc) Ensure AI observability—tracing, logging, monitoring, and drift detection Leadership & Communication Lead technical teams and mentor engineers Communicate complex concepts to non‑technical stakeholders Run architecture reviews, design workshops, and governance #J-18808-Ljbffr