ABOUT US
We’re the world’s leading provider of secure financial messaging services, headquartered in Belgium. We are the way the world moves value – across borders, through cities and overseas. No other organisation can address the scale, precision, pace and trust that this demands, and we’re proud to support the global economy.
We’re unique too. We were established to find a better way for the global financial community to move value – a reliable, safe and secure approach that the community can trust, completely. We’re always striving to be better and are constantly evolving in an ever-changing landscape, without undermining that trust. Five decades on, our vibrant community reflects the complexity and diversity of the financial ecosystem. We innovate diligently, test exhaustively, then implement fast. In a connected and exciting era, our mission has never been more relevant. Swift now has a presence in 200+ countries and legal territories to serve a community of more than 12,000 banks and financial institutions.
As Senior Technical Lead of the AI & Analytics Ops squad, you will be responsible for driving engineering excellence, ensuring platform security compliance, and guiding the squad’s technical direction for operating AI workloads at scale.
Your mission is to ensure that AI use cases are reliably deployed, monitored, and maintained across their full lifecycle—while applying best engineering practices and adhering to rigorous security standards.
You will work closely with platform teams, data scientists, ML engineers, and the broader AAA tribe.
Key Responsibilities
- Lead technical decisions for the squad’s AI operational workloads (deployment, automation, monitoring, drift detection, retraining pipelines, etc.).
- Ensure adherence to modern software engineering best practices (code quality, testing, CI/CD, observability, security-by-design).
- Review and guide Python codebases, ensuring maintainability and performance.
- Provide mentorship to engineers and support continuous improvement within the squad.
- Oversee the full operational lifecycle of AI models:
- deployment
- monitoring
- performance tracking
- drift detection & alerts
- triggering or coordinating retraining cycles
- Guarantee availability and reliability targets for live models.
- Participate in the on‑call rotation and drive incident response, mitigation, and RCA improvements.
- Ensure that all squad deliverables comply with SWIFT operational and security standards (ACF v6, TOEF, SEP, DOR, etc.).
- Enforce secure practices for deployment, secret management, access control, and data handling.
- Collaborate with governance, security, and platform teams to align on internal policies and controls.
- Lead the squad’s implementation of automation across the stack:
- Jenkins CloudBees , CDRO , Ansible
- Helm ‑based deployments into OpenShift
- Secret management via Vault
- Storage on S3 Cloudian
- Monitoring via Ansible , dashboards, and operational metrics
- Identify opportunities to increase automation maturity (e.g., fully automated retraining, automated drift detection, integration with MLOps frameworks).
- Work closely with:
- Platform/infrastructure squads (who define the environment strategy)
- Data Science squads (for model lifecycle workflows)
- Governance, Security, Responsible AI, and Architecture teams
- Translate tribal OKRs into actionable technical plans for the squad.
Bachelor’s or Master’s degree in Computer Science , Software Engineering , Information Security , Data Engineering , or a related technical field.
- Strong hands-on experience in Python for production‑grade systems.
- In‑depth knowledge of Kubernetes/OpenShift and Helm deployment patterns.
- Experience with CI/CD pipelines using Jenkins CloudBees and CDRO.
- Strong understanding of Ansible for automation & orchestration.
- Experience with Vault for secrets management and secure configuration.
- Solid understanding of object storage (S3/Cloudian) and file‑based AI workloads.
- Proven experience applying secure engineering standards in production environments.
- Knowledge of operational risk controls, incident processes, and audit/traceability requirements.
- Experience working with data science workflows (model training, inference, validation).
- Understanding of:
- drift detection
- model retraining triggers
- automated pipelines for ML model lifecycle
- Exposure to MLOps principles and production practices.
- Demonstrated experience providing technical leadership within a squad or engineering team.
- Strong communication skills to interact across architecture, data science, security, and Ops layers.
- Ability to translate complex technical topics into actionable squad‑level initiatives.
What we offer
We give you the freedom to be yourself. We are creating an environment of unique individuals – like you – with different perspectives on the financial industry and the world. A diverse and inclusive environment in which everyone’s voice counts and where you can reach your full potential.
We are committed to an inclusive and accessible recruitment process. If you require a reasonable accommodation related to accessibility during your application or interview, please contact [email protected] or indicate this in your application.
Please note that this mailbox is not monitored for general recruitment enquiries and should only be used for accessibility or accommodation-related requests (for example related to vision, hearing or neurodiversity).
All requests are confidential and will not affect your candidacy.
Don’t meet every single requirement? At Swift, we are dedicated to building a workplace where people can bring their full selves and ideas to the team, so if you are excited about this role, we encourage you to apply even if you do not meet every single qualification.
