ey Responsibilities
1. Architecture & Platform Design
- Architect a scalable, modular, and extensible platform to support evolving regulatory use cases across multiple markets
- Define architectural standards, design patterns, and best practices across the CARBON platform
- Establish and enforce product governance including change control, versioning, and prevention of customisation creep
- Translate business needs into a cohesive product strategy and technical design framework
- Evaluate and incorporate emerging technologies — with a particular focus on AI/ML capabilities — to enhance platform performance and intelligence
2. AI-First Design & Development
- Lead the architectural design of the platform with an AI-first approach — ensuring AI and ML are embedded at the core of data processing, compliance automation, anomaly detection, and regulatory intelligence
- Define and implement AI-assisted development workflows: leveraging tools such as GitHub Copilot, Cursor, Amazon CodeWhisperer, or equivalent AI coding assistants to accelerate engineering velocity and improve code quality
- Establish standards for the use of AI tools across the development lifecycle — from requirements analysis and design through to code generation, testing, and deployment
- Drive adoption of AI-powered testing, automated code review, and intelligent CI/CD pipelines within the engineering team
- Identify use cases within the CARBON platform where LLM-based capabilities (e.g., natural language querying of compliance data, AI-assisted report generation, intelligent validation) can deliver measurable business value
- Stay current with the rapidly evolving AI tooling landscape and provide technical leadership in evaluating and adopting new capabilities responsibly
3. Product Strategy & Governance
- Define and drive the product roadmap in alignment with business priorities and regulatory requirements
- Partner with engineering, delivery, and business teams to ensure consistent execution and adherence to product principles
- Establish architectural guardrails to maintain platform integrity across all customer implementations
- Reduce dependency on project-level customisations by strengthening core product configurability
- Build, mentor, and scale product and engineering teams as the platform grows
4. Delivery & Cross-functional Collaboration
- Work closely with product managers, implementation leads, and customer-facing teams to align architecture with real-world delivery requirements
- Perform code and architecture reviews to ensure quality, consistency, and adherence to defined standards
- Support pre-sales and solutioning activities — contributing to RFPs, client presentations, and technical due diligence
- Flexibility and willingness to travel domestically and internationally as required to support business and project needs
Key Skills & Experience
Technical Expertise
- 10-15 years of experience spanning Solution Architecture and Product / Technology leadership, bridging business and engineering domains
- Expertise in API-first design, microservices architecture, and cloud-native platforms (AWS / Azure / GCP)
- Strong proficiency in Java, Python, Node.js, and Angular; solid understanding of modern software engineering practices
- Solid understanding of data architecture, reporting frameworks, and compliance-driven systems
- Hands-on experience with CI/CD pipelines, DevOps practices, and infrastructure-as-code
- Solid understanding of IT infrastructure with experience deploying applications across on-premises and cloud environments
AI & Emerging Technologies
- Demonstrated experience designing systems with an AI-first approach — integrating ML models, LLMs, or intelligent automation into production platforms
- Hands-on familiarity with AI-assisted development and deployment tools (e.g., GitHub Copilot, Cursor, Amazon CodeWhisperer, Tabnine, or similar)
- Exposure to MLOps practices: model versioning, deployment pipelines, monitoring, and governance of AI models in production
- Working knowledge of prompt engineering, RAG (Retrieval-Augmented Generation) architectures, or fine-tuning approaches for domain-specific compliance use cases is a strong advantage
- Experience evaluating and integrating third-party AI/ML services (OpenAI, Azure OpenAI, AWS Bedrock, or equivalent)
Domain & Soft Skills
- Experience in RegTech, SupTech, or financial regulatory / reporting platforms is highly preferred
- Experience in defining governance frameworks, architectural guardrails, and product standards
- Excellent problem-solving, communication, and decision-making capabilities in complex, multi-stakeholder environments
- Minimum one architecture-level certification (Java, Cloud, TOGAF, or equivalent)
