AI SDLC (Software Development Lifecycle) Architect

Overview We are looking for an AI SDLC Architect to shape how software gets built at Susquehanna in an AI-native world. Working within the Enterprise AI Architecture group, the AI SDLC Architect builds a firm-wide picture of current software development and quantitative research workflows, distills them into SDLC archetypes, and defines the capabilities needed to reach an AI-native target state.

About Susquehanna International Group, LLP

• Susquehanna is a global quantitative trading firm built on deep research, cutting-edge technology and a collaborative culture.
• We build most of our systems from the ground up, and innovation drives everything we do.
• As the AI SDLC Architect in the Enterprise AI Architecture group, you'll help define how software gets built at Susquehanna in the age of AI.

Responsibilities

• You’ll Do Build the current-state picture.
• Discover how software is built across a highly heterogeneous landscape of code producers.
• Define the SDLC archetypes.
• Condense dozens of team mappings into a verified map of how software is delivered and distill it into a set of archetypes with similar requirements.
• Describe the target state from the team's perspective.
• For each archetype, set out what an AI-native workflow looks like in practice: where AI-assisted development, agents and automated checks fit, what each should do for the team, and what good looks like when it works.
• Own the capability backlog.
• Translate the gap between current and target state into a prioritized set of platform capabilities, each with clear functional requirements, acceptance criteria and a rationale.
• Be the voice of the teams throughout delivery.
• Keep requirements flowing.
• Maintain the channel between the globally distributed development and research teams and the Architecture group, continuously gathering, structuring and triaging their SDLC and platform needs into the backlog.
• Validate and steer.
• Pilot new capabilities with teams, gather feedback, and measure whether they deliver the intended outcomes.
• Use what you learn to reorder priorities and refine the archetypes.
• Experience owning requirements and priorities for a platform and enterprise tooling, from discovery through acceptance.
• Outcome-oriented.
• Defines success in terms of team outcomes such as cycle time, quality and adoption, and uses them to steer priorities.
• Strong, adaptable communicator with technical credibility, who can build trust with development and quantitative research teams and bring senior stakeholders to a decision.
• Why Join Us?
• You'll work with software engineers and quantitative researchers to understand how they work today and start to shape an AI-native SDLC that meets their future needs.

Requirements

• What we’re looking for First-hand experience with the full software development lifecycle, and a solid understanding of how its phases vary across different kinds of teams.
• Ability to bring structure to highly ambiguous and highly complex technical environments.
• Working knowledge of AI-native software development.
• You know concepts like spec-driven development, agent harnesses, verification design, autonomy tiers and policy-as-code well enough to specify what automation should do for a team and to evaluate the proposals engineers bring back.