Director of Software Engineering and ML - Agentic Commerce - Executive Director
Salary not listed • LONDON, United Kingdom • Full-time
Posted 18d ago
Job Location
LONDON, United Kingdom
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
We are seeking a Director of Software Engineering and ML to lead a London-based team of software, data, and ML engineers. This role involves building B2B agentic commerce agents and productionizing the ML models they utilize as tools. You will be responsible for delivery, people management, and technical direction, ensuring the safe deployment of AI agents for corporate clients on the firm's governed agent platform. This is an opportunity to push the boundaries of what's possible in AI-driven commerce and make a significant impact on client solutions.
Responsibilities
- Build and lead the London engineering team, including hiring, coaching, career development, and performance management.
- Own the delivery roadmap for B2B agentic commerce agents from initial production release to scaling.
- Set technical direction for multi-agent architecture, deterministic control of pricing and policy, evaluation, and observability.
- Establish the operational model for ML in production, covering training, testing, deployment, monitoring, and retraining.
- Lead the team through model risk, cybersecurity, and control reviews for agent and model deployment.
- Partner with platform teams, client channels, and business stakeholders, contributing reusable components.
- Drive adoption of AI-assisted engineering practices to improve code quality and delivery speed.
- Make decisions regarding team resources, budget, vendor selection, and tactical operations.
- Lead evaluation sessions with external vendors and internal teams for architectural designs and technical credentials.
- Communicate progress, risks, and trade-offs clearly to senior leadership.
- Contribute to a team culture of diversity, opportunity, inclusion, and respect.
Requirements
- Formal training or certification in software engineering concepts and advanced applied experience.
- Significant experience leading and developing engineering teams.
- Hands-on experience delivering system design, application development, testing, and operational stability.
- Hands-on development background in Python and/or Java, with sufficient depth for technical discussions.
- Strong understanding of concurrency and distributed computation, including failure modes.
- Experience leading the delivery of production AI/ML systems, ideally including LLM-based applications or agents.
- Strong understanding of the ML lifecycle in production: data pipelines, training, deployment, monitoring, and governance.
- Demonstrated experience leading effective use of AI-assisted software development tools and setting validation standards.
- Strong understanding of responsible AI use, including data sensitivity, secure handling, and adherence to resiliency and security expectations.
- Advanced understanding of agile methodologies like CI/CD, Application Resiliency, and Security.
- Practical cloud-native experience with Kubernetes and Amazon EKS, micro-VM isolation, and sidecar patterns.
- Ability to influence across organizational boundaries and communicate with executive audiences.
- Experience with agent frameworks and protocols (MCP, A2A, Google ADK, LangGraph) and agent evaluation practices.
- Experience with Databricks, MLflow, and model serving on Kubernetes in AWS.
- Experience delivering AI systems through model risk management or equivalent regulatory review.
- Experience running a team within a federated platform model.
- Domain knowledge of B2B payments, commercial card, accounts payable, supplier enablement, or KYC onboarding.
- Track record of building and scaling engineering teams, including hiring senior engineers and developing leaders.
- In-depth knowledge of the financial services industry and their IT systems.