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IRIS - Technical Lead - AI/ML Platform

IRIS Business Services
12 - 18 Years
Multiple Locations

Posted on: 21/10/2026

Job Description

Role Overview:

We are seeking a seasoned Technical Lead to own the end-to-end architectural vision for the IRIS Carbon platform. This role is critical in ensuring a clear separation between core product development and project delivery, while driving scalability, consistency, and long-term product sustainability.

A defining requirement of this role is an AI-first architectural mindset - the ability to design systems, workflows, and development pipelines that embed artificial intelligence and automation as foundational elements, not afterthoughts. The ideal candidate is equally comfortable shaping product strategy and getting hands-on with code, design reviews, and AI-assisted development tooling.

Key Responsibilities:

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.

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.

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.

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).

Expected Outcomes:

- A well-governed product lifecycle with clear ownership, decision-making frameworks, and AI-embedded engineering standards.

- A scalable, robust, and consistent platform architecture across all CARBON implementations.

- Measurable improvement in engineering velocity through AI-assisted development tooling and automated workflows.

- Reduced dependency on project-level customisations, preserving core product integrity.

- Improved alignment between business goals, product evolution, and technical execution.

- A future-ready platform with AI capabilities that deliver tangible value to regulators and enterprises.

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