AI Data and Solution Architect

• Provide strategic leadership and hands-on oversight for a large-scale data-to-AI transformation programme, ensuring architecture decisions align with AWS best practices and fintech regulatory requirements.
• Design, review, and govern agentic AI systems and LLM-powered workflows (Claude, GPT, or similar) end-to-end: prompt engineering, tool calling, multi-step reasoning, retries, fallbacks, and state management.
• Architect and steer the build of scalable data pipelines and AI/ML platforms on AWS (Glue, Lambda, SageMaker, Bedrock), with deep involvement in distributed computing, performance, and cost optimisation.
• Own the technical roadmap and mentor delivery teams; if the AI platform is misaligned, unscalable, or non-compliant, it is on you.
• Influence C-level stakeholders and engineering teams directly, translating complex AI architecture into clear business outcomes and risk-mitigated execution plans.
• Work autonomously to programme deadlines with minimal hand-holding; this is a strategic leadership role, not a task-execution role.

• 12+ years in data engineering, AI/ML, or cloud architecture.
• 8+ years leading large-scale data transformation initiatives (minimum 3 engagements delivered).
• 5+ years hands-on with generative AI, LLMs, or agentic AI systems in production.
• 3+ years deep AWS experience (Glue, Lambda, SageMaker, Bedrock) with proven AI/ML platform implementations.
• Expert-level knowledge of agentic AI architecture and design patterns; hands-on experience with Claude API or similar LLM APIs.
• Highly proficient in Python and PySpark; strong understanding of distributed computing and scalability patterns.
• Solid experience with data pipeline orchestration (Airflow, Step Functions, or equivalent) and ETL/ELT patterns at scale.
• Executive presence and demonstrated ability to influence C-level stakeholders and make decisions under uncertainty.
• Proven mentoring and knowledge transfer experience; you must uplift the team, not just direct it.

Preferred background (strong signals)

• Financial services background and experience with regulated industries (banking, insurance, or fintech).
• Direct knowledge of PCI-DSS, FCA, SOX, and/or GDPR compliance requirements in AI/data contexts.
• Experience with Ab Initio or similar legacy ETL platforms; familiarity with large-scale migration scenarios (5,000+ jobs).
• Previous engagements with Capital One or similar Tier 1 financial institutions.
• AWS Certified Solutions Architect - Professional and/or AWS Certified Data Analytics - Specialty.
• Experience with AWS Incident Detection & Response (IDR), data governance, metadata management, and cost optimisation.
• Track record of delivering complex programmes on-time and within budget.

What will get you rejected

• Less than 5 years of production generative AI/LLM experience; tutorials and side projects are not enough.
• No proven track record of successful AI/ML platform implementations at enterprise scale.
• “I designed it, someone else delivers it” mindset; this role requires both strategic oversight and deep technical credibility.
• Poor references or a history of missed commitments.
• Lack of executive presence or inability to communicate trade-offs clearly to technical and non-technical audiences.
• Needs detailed specs before forming an opinion; this role demands decision-making under uncertainty.