Define the architecture and roadmap for the DevEx Strategy domain: reusable service templates, code starter kits, libraries, SDKs, and micro frontend patterns.
Design and deliver a generic AI integration framework that enables application teams to plug into standard interfaces for data, model orchestration, and UI surface (micro frontends) without bespoke engineering per app.
Produce reference architectures, blueprints, and hands-on starter projects (backend + frontend + CI/CD + observability) that accelerate new projects.
Build and maintain reusable components: APIs, SDKs/jars, libraries; keep them secure, documented, and versioned.
Lead PoCs and prototype solutions that validate architectural approaches and evaluate new technologies (cloud, AI platforms, orchestration tools).
Drive cross-team collaboration to ensure the templates and frameworks meet real product needs and evolve with feedback.
Establish standards and best practices around service design, API contracts, authentication/authorization, data access, testing, release automation, and monitoring.
Mentor and guide engineering teams and architects across the organization on adoption of the frameworks and patterns.
Partner with product, security, infrastructure and data teams to ensure governance, privacy, compliance, and performance goals are embedded in platform capabilities.
Participate in architecture reviews and help teams migrate from legacy approaches to standardized solutions.
Own technical documentation, developer onboarding flows, and demos to help adoption.
Requirements
6+ years of professional software engineering experience with progressive ownership over architecture and platform initiatives.
Strong architecture background: microservices, event-driven systems, domain-driven design, API design and governance.
Hands-on experience building reusable libraries/SDKs, starter kits, and reference implementations for other engineering teams to consume.
Solid cloud experience with cloud (preferably AWS) — design for scalability, reliability and cost-efficiency.
Practical experience with Docker and CI/CD pipelines.
Backend expertise in Java / Spring (or equivalent) and demonstrable knowledge of service packaging (jars), dependency management, and versioning.
Frontend proficiency (Angular, or similar) and experience with micro frontend architectures and patterns.
Experience designing and consuming RESTful APIs.
Strong understanding of data integration patterns and connectors for domain datasets.
Familiarity with observability tools (metrics, tracing, logging) and operational excellence practices.
Demonstrated ability to lead cross-functional technical initiatives and mentor engineers.
Excellent communication skills; able to translate architectural tradeoffs for technical and non-technical stakeholders.
Experience designing frameworks or platforms for AI/ML integration (LLM orchestration, model calling patterns, prompt management, etc.).
Experience with AI/ML lifecycle tooling or ML platforms (SageMaker, Hugging Face, OpenAI/Anthropic APIs, etc.).
Knowledge of prompt engineering, retrieval-augmented generation (RAG), embedding stores, and data privacy/safety considerations for AI.
Familiarity with event streaming platforms and data pipelines.
Strong security and compliance mindset (IAM, encryption, secure coding practices).