AI SDLC (Software Development Lifecycle) Architect

Overview

What 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.

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.

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?

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. 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.