The DevEx Strategy team creates the foundations and guardrails that let product and application teams move fast and safely. We design and maintain reusable starter kits, service and UI templates, runtime libraries, and the integration frameworks teams depend on. Our mission is to remove duplication, standardize best practices, and provide a plug-and-play approach for enabling capabilities — including AI — across AntiFraudAnalytics.
We’re hiring an Architect / Principal Engineer who can own the technical vision and delivery of reusable platform building blocks and an organization-wide AI integration framework. This person will design end-to-end reference architectures, starter kits, common services (APIs / jars / libraries), micro frontend patterns, and developer-facing tooling so that teams can adopt common capabilities with minimal friction. You will also drive the strategy and pragmatic adoption of AI across products by defining patterns for connecting domain data, orchestrating model calls, surfacing AI results in micro frontends, and ensuring secure, observable, and maintainable integrations.
- 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.
Required Qualifications & Skills
- 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.
Preferred / Nice-to-Have
- 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).
- Open source experience or community contributions to developer tooling.
Education & Experience
- BS/MS in Computer Science, Engineering or equivalent practical experience.
- 6+ years of software development experience; 3+ years in architect/lead technical roles strongly preferred.
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