Principal Agentic Engineer Talent Pipeline

Full-Stack Architecture & Technical Vision

• Envision and architect end-to-end solutions for complex enterprise-scale projects spanning frontend backend services APIs data pipelines and cloud infrastructure.

• Provide clear technical direction across the full stack; ensure quality coherence and alignment of all technical solutions with business objectives.

• Champion the design and implementation of highly scalable secure and maintainable software systems API-first cloud-native and composable by default.

• Own technical decisions across layers: from UI and component architecture to service design data modelling and infrastructure configuration.

• Guide technology decisions that align with both business objectives and Applys standard of engineering excellence.

Agentic Engineering & AI-Native Delivery

• Organize distribute and translate backlog requirements into detailed spec-driven requirements that coding agents can implement autonomously.

• Synthesize user stories site maps content strategy design systems and brand strategy into specifications that guide agent-driven development.

• Apply spec-driven development (e.g. BMAD Method or equivalent) to ensure clarity consistency and quality across agent-orchestrated workflows.

• Architect full-stack solutions across UI APIs services and data stores that integrate seamlessly with AI-powered systems including LLM APIs RAG pipelines and agent orchestration frameworks.

• Design both user-facing experiences and backend service contracts that help products express goals constraints and context clearly to AI agents.

• Integrate AI-powered APIs LLM-driven features RAG-based experiences and AI-assisted developer workflows throughout the full application stack.

Platform Cloud & Composable Architecture

• Design and implement microservices APIs and composable architectures using modern cloud platforms (GCP preferred; AWS/Azure experience valued).

• Build and maintain backend services data pipelines and integrations with composable platforms: Contentful Contentstack Algolia Cloudinary commercetools and similar MACH ecosystem products.

• Implement enterprise-grade design systems content models component libraries and the backend services that power them.

• Ensure systems are performant and well-instrumented across all layers from client-side rendering and GEO to API latency caching and data integrity.

• Leverage containerization (Docker) orchestration (Kubernetes) serverless patterns and infrastructure-as-code where appropriate.

Technical Leadership & Mentorship

• Serve as a technical visionary shaping the engineering culture and raising technical standards across multiple teams and practices.

• Mentor and guide engineers in best practices: architectural decision-making spec-driven development AI-assisted workflows and engineering craft.

• Foster a culture of continuous learning innovation psychological safety and engineering excellence.

• Lead by example demonstrating humility curiosity and deep professional commitment.

Collaboration & Communication

• Collaborate with Technology Directors Engineering Managers Product UX and cross-functional stakeholders to shape and deliver solutions.

• Partner with Project Managers and client stakeholders to manage delivery risks timelines and expectations.

• Communicate complex technical and AI concepts clearly to varied audiences from engineers to non-technical clients.

• Influence across multiple teams and practices through technical leadership and collaborative synergy.

Engineering Experience & Foundation

• 10 years of software engineering experience across the full stack with demonstrated technical leadership at Staff or Lead level.

• Proficiency in TypeScript and modern JavaScript; hands-on experience with React and on the frontend and or similar runtimes on the backend.

• Proven ability to design build and maintain RESTful and/or GraphQL APIs and backend services not just consume them.

• Experience with relational and/or NoSQL databases: schema design query optimization and data modelling for production systems.

• Deep understanding of API design microservices cloud-native architectures and headless/composable systems (MACH principles).

• Extensive experience with cloud platforms (GCP preferred; AWS or Azure also valued) and their associated services.

• Experience with containerization (Docker) orchestration (Kubernetes) and serverless computing.

• Familiarity with Git CI/CD workflows and production deployment practices.

• Strong system design fundamentals across layers: API contracts data flow caching strategies auth patterns and performance optimization at scale.

Agentic & AI Capabilities

• Hands-on experience working with AI coding agents (e.g. Claude Code GitHub Copilot) in production delivery workflows.

• Strong prompt engineering skills and ability to write high-quality agent specifications.

• Demonstrated experience with LLMs (e.g. Claude Opus Gemini GPT-4/5) in real-world application development.

• Experience with vector stores and RAG-powered applications.

• Experience with Agent Development Kits (e.g. Google ADK) or similar orchestration frameworks.

• Familiarity with Vertex AI Google Gen AI APIs or equivalent AI platform tooling.

• Genuine curiosity and passion for Generative AI with a desire to make it a core focus of your career.

Leadership & Professional Skills

• Proven track record of leading complex enterprise-scale software projects with high autonomy.

• Demonstrated ability to mentor and grow engineers resolve technical conflicts and drive alignment.

• Exceptional communication skills written and verbal with the ability to explain complex concepts to non-technical stakeholders.

• Strategic problem-solving ability with comfort navigating ambiguous goals and translating them into clear technical direction.

• Experience working effectively in fully remote distributed team environments.

• Background in a consultancy or professional services firm is strongly preferred.

• Experience with BMAD Method or similar spec-driven development frameworks.

• Experience with AI agent design patterns task planning and reasoning.

• Experience with agent observability and debugging.

• Familiarity with layered and distributed architectures.

• Experience with Terraform or infrastructure-as-code practices.

• Experience across mobile platform engineering or testing domains in addition to full-stack web.

• Experience with eCommerce platforms (e.g. commercetools CommerceLayer) end-to-end from storefront to order management APIs.

• Familiarity with Lean and Agile principles and frameworks.

• Experience contributing to business development and technical strategy initiatives.

• Track record of driving innovation through emerging technology adoption.