AI-Enabled Product Engineer – Aladdin, Investments & Trading Engineering, Vice President

Vice President, AI-Enabled Product Engineer – Aladdin, Investments & Trading Engineering 

Location: Edinburgh 

About the Role 

BlackRock is seeking a Vice President, AI-Enabled Product Engineer to join Aladdin, Investments & Trading Engineering within Analytics & Compliance Engineering. This role is for a hands-on engineering leader who can build scalable agentic solutions while helping accelerate the adoption of AI-enabled engineering practices across the product development lifecycle. 

The successful candidate will work at the intersection of investment technology, investment compliance workflows, full-stack engineering, and applied AI. They will help design and deliver capabilities across the Aladdin platform that support investment professionals, compliance teams, and business stakeholders operating in complex global markets. 

About Aladdin, Investments & Trading Engineering 

Aladdin is BlackRock’s technology platform used by investment professionals to manage portfolios, analyse risk, execute workflows, and make decisions at scale. Within Investments & Trading Engineering, Analytics & Compliance Engineering develops technology that helps teams manage investment guidelines, regulatory obligations, analytics-driven workflows, and operational controls across global markets. 

The Investment and Trading Compliance Engineering team is responsible for developing and maintaining tools to ensure that organizations using Aladdin® comply at different stages of the asset management process. This includes ensuring that clients follow guidelines established internally, by themselves, and by the market regulators. The system accomplishes this through high-throughput rule-based compliance engines, which sit at the heart of the investment system and process millions of calculations per day. 

Our engineering teams build products with real reach, real complexity, and real impact. We are evolving our platform with persona-based, workflow-driven experiences, modular architecture, resilient services, and responsible AI capabilities that improve productivity, decision-making, knowledge discovery, and operational efficiency. 

What You’ll Do 

• Design, build, and deliver high-quality full-stack Agnetic product capabilities across the Aladdin platform, with a focus on Analytics & Compliance Engineering workflows. 

• Act as a hands-on technical leader across the product development lifecycle, contributing to technical design, implementation, testing, deployment readiness, production support, and continuous improvement. 

• Partner with product managers, engineers, compliance specialists, and business stakeholders to translate complex business problems into clear specifications, technical designs, delivery plans, and actionable Agile backlogs. 

• Apply AI-enabled engineering practices to accelerate design exploration, prototyping, software development, testing, code review, documentation, and operational support. 

• Help embed responsible AI capabilities into product workflows and platform services, including intelligent assistants, workflow automation, semantic search, knowledge retrieval, and reasoning over compliance and investment information. 

• Build scalable, resilient, and operable systems that balance functional requirements with non-functional concerns such as performance, latency, reliability, security, observability, and maintainability. 

• Influence architecture and technical direction across initiatives, articulating design trade-offs and aligning stakeholders around pragmatic engineering choices. 

• Champion engineering excellence through test-driven development, behaviour-driven development, DevOps practices, production readiness, and an SRE mindset. 

• Mentor engineers, raise the bar for technical quality, and contribute to a culture of continuous learning, innovation, accountability, and collaboration across a global engineering organisation. 

Qualifications 

• Degree in Computer Science, Engineering, Mathematics, or a related STEM discipline, or equivalent professional experience. 

• 8+ years of professional software engineering experience, including experience delivering enterprise-scale systems in production. 

• Strong full-stack engineering background, with hands-on experience in modern backend and frontend technologies. 

• Proven ability to lead technical initiatives, shape ambiguous problem spaces, define execution plans, and deliver outcomes through collaboration with cross-functional partners. 

• Strong understanding of software engineering fundamentals, distributed systems, APIs, data flows, event-driven architecture, and resilient platform design. 

• Experience applying modern Agile, DevOps, and engineering excellence practices to improve delivery quality, team productivity, and operational outcomes. 

• Excellent communication, influencing, and stakeholder management skills, with the ability to explain complex technical concepts clearly to technical and non-technical audiences. 

Skills and Experience 

• Hands on experience with AI enabled SDLC / PDLC practices, including: 

• Using AI to accelerate design exploration, prototyping, and architectural decision making 

• Applying AI assisted development, testing, code review, and documentation practices 

• Embedding AI capabilities into product workflows and platform services responsibly and securely 

• Frameworks such as Devin / Windsurf, Cursor or GitHub Copilot 

• Hands-on full stack experience with Java or other modern backend languages, and frontend frameworks such as React or Angular. 

• Experience designing and operating APIs, microservices, distributed systems, and event-driven architectures at enterprise scale. 

• Exposure to Generative AI, large language models, retrieval-augmented generation, semantic search, embeddings, knowledge retrieval, or agentic workflow patterns. 

• Strong focus on software quality, including automated testing, TDD, BDD, code review discipline, observability, resiliency, and production support. 

• Ability to reason about scalability, reliability, security, cost, maintainability, and delivery velocity when making technical decisions. 

• Experience working in large, global engineering organisations and collaborating across locations, time zones, product areas, and stakeholder groups. 

• Ability to build domain context quickly and translate investment, analytics, or compliance workflows into robust product and platform capabilities. 

Preferred Experience 

• Experience in financial services, investment technology, compliance technology, regulatory technology, portfolio management, trading, or enterprise SaaS platforms. 

• Familiarity with compliance workflows, investment guidelines, rule intelligence, regulatory obligations, or controls-oriented technology. 

• Experience with cloud-native or hybrid architectures, containerisation, Kubernetes, observability platforms, CI/CD, and modern platform engineering practices. 

• Experience with AI governance, responsible AI principles, evaluation frameworks, model quality metrics, or monitoring of AI-enabled systems. 

• Exposure to domain-driven design, micro frontend architectures, platform strategies, or modular product architectures that enable multiple teams to deliver independently and consistently.