Education

University degree in Computer Science, Information Systems, or a related field; or equivalent work experience. Masters degree an asset.

Experience

Typically has 6 to 10 years of relevant work experience.

Domains

Job Responsibilities

Run frontier AI models directly against SWIFT's codebases to find vulnerabilities that conventional tools miss

Build the methodology for this work through direct experimentation.

Build the pipeline that makes AI-assisted detection usable at scale: this includes writing the logic that validates findings, cuts duplicates, and routes real issues to remediation

Run head-to-head technical evaluations of frontier models on real detection tasks, and let the evidence from testing decide which models and techniques SWIFT relies on.

Build the integration that plugs AI-assisted detection into how SWIFT develops software, working alongside existing security tooling

Find the vulnerability classes current tooling structurally cannot see, and build the detection approach to catch them ahead of where the rest of the industry is

Work entirely within SWIFT's governed access and tooling controls

Defend technical decisions under scrutiny from AI and Security peers, and document the methodology so it survives

Required Qualifications/Skills

Demonstrated hands-on experience applying AI/LLM models to real security testing or vulnerability research

Strong software engineering ability: can read, navigate, and reason about large, unfamiliar codebases directly, across multiple languages.

Deep working knowledge of application security fundamentals: common vulnerability classes, exploit mechanics, and how static, dependency, and dynamic analysis tools actually work and where they fail.

Proven ability to build working tools and pipelines from scratch, not just configure existing ones: scripting, automation, and integration work is core to this role

Experience designing and running structured technical evaluations or experiments (model comparisons, A/B testing, or equivalent) and drawing defensible conclusions from the results.

Comfortable operating with significant ambiguity and no established playbook; able to originate a technical approach rather than execute a known one.

Clear technical communication: able to document and defend complex technical decisions to peer security engineers under scrutiny.

Preferred Qualifications

Experience working in a regulated or high-assurance environment (financial services, critical infrastructure, defense, healthcare, or similarly regulated sectors).

Familiarity with multiple frontier AI model families (e.g., GPT-class, Claude-class) and their differing strengths for security-related tasks.
Prior experience contributing to or building a security capability that didn't previously exist, rather than operating an established one

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.