AI SDLC (Software Development Lifecycle) Architect
Core
Define firm-wide SDLC archetypes and capabilities to transition software development and quantitative research workflows to an AI-native state.
Role type
Senior IC AI SDLC Architect
Builds
Enterprise SDLC archetypes, platform capability backlogs, and AI-native workflow definitions
Domain
Quantitative finance + AI-native software development
Deliverable
production ML models
Required skills
SDLC lifecycle expertise, AI-native development concepts, requirements ownership, outcome-based prioritization, complex environment structuring
Preferred skills
Spec-driven development, agent harnesses, verification design, autonomy tiers, policy-as-code
Technologies
AI agents, automated checks, policy-as-code frameworks
Responsibilities
Map current-state software development workflows across heterogeneous teams, define target-state AI-native workflows, own capability backlog with functional requirements, maintain communication channels between distributed teams and architecture group, pilot new capabilities and measure outcomes
Seniority
Senior, hands-on IC
