Principal AI Engineer – AWS Kiro Platform

Job Title

Responsibilities:

Spec-Driven Development with Kiro — Lead the adoption of AWS Kiro's spec-first approach, authoring structured requirements, design, and task specifications that drive autonomous, traceable code generation — ensuring every line of generated code is grounded in validated intent.

Agent Hooks & Automation Design — Design and implement Kiro agent hooks (file-save triggers, event-driven automations) that autonomously enforce coding standards, run linting, regenerate documentation, and invoke downstream agents — reducing manual toil across the development lifecycle.

Steering File Governance — Define and maintain Kiro steering files (.kiro/steering/) to encode organisational standards, architectural patterns, tech stack conventions, and security guardrails — ensuring every AI-assisted task aligns with enterprise engineering policies.

Multi-Agent Workflow Orchestration — Architect multi-agent pipelines within Kiro where specialised sub-agents handle discrete SDLC concerns — requirements analysis, API contract generation, code scaffolding, test creation, and deployment validation — with clear handoffs and human-in-the-loop checkpoints.

AI-Assisted Architecture & Design Artefacts — Utilise Kiro's agentic capabilities to auto-generate architecture decision records (ADRs), API specifications (OpenAPI), data models, and system design documents from high-level requirements — accelerating the design phase significantly.

Automated Test Generation & Quality Engineering — Leverage Kiro agents to automatically generate unit tests, integration tests, BDD scenarios, and test data aligned to spec definitions — continuously improving coverage and shifting quality further left in the pipeline.

CI/CD & Dev Sec Ops  Integration — Integrate Kiro agent workflows with CI/CD pipelines, connecting spec-driven outputs to automated build, security scanning (SAST/SCA), and deployment stages — creating a seamless, auditable path from spec to production.

Prompt & Spec Engineering Excellence — Develop reusable, parameterised spec templates and prompt patterns tailored to domain-specific engineering contexts (microservices, cloud-native, event-driven architectures) — enabling consistent, high-quality AI outputs at scale.

Engineering Best Practices & AI Governance — Establish standards for responsible agentic development including output validation, hallucination mitigation, spec versioning, agent observability, and change traceability — ensuring AI-generated artefacts meet the same rigour as human-authored code.

Innovation, Enablement & Community — Stay at the forefront of AWS Kiro evolution and the broader agentic AI ecosystem (Amazon Q, Bedrock Agents, MCP integrations), run internal enablement sessions, publish reusable Kiro templates, and champion spec-driven agentic engineering across the organisation.

Skills & Experience:

Hands-on experience with AWS Kiro

Strong understanding of spec-driven development, requirements engineering, and SDLC governance

Proficiency in AWS services (Bedrock, Lambda, CDK, ECS/EKS) and cloud-native architecture patterns

Experience designing multi-agent systems with agent orchestration, tool use, and MCP integrations

Solid software engineering background across at least one major stack (Java/Spring, Python, Node.