Senior Staff Software Engineer, AI Developer Experience

The role:

SoFi's AI Platform team builds the foundation that lets every engineer at SoFi ship faster, safer, and with more leverage from AI. Our AI Developer Experience (AI DevEx) team owns SoFi's interactive coding strategy and the underlying infrastructure: AI economics, coding harnesses and harness vending, our evaluation platform, the AI Gateway, and intelligent model routing. 

As a founding Senior Staff Software Engineer, you'll be the technical lead and subject matter expert for this area across AI Platform: setting architecture, shaping the interactive coding strategy, and leading work across Autonomous Coding, CI/CD, Code Factory, and our customer engineering teams.

What you’ll do:

• Set Technical Direction: Define and drive the architecture for the enterprise AI Gateway, model routing, automated evaluation platform, and harness vending, ensuring seamless support for interactive and autonomous workflows across multiple business units.

• Shape Strategy & Roadmaps: Proactively identify systemic developer productivity bottlenecks, translate opportunities into a 12–24 month technical roadmap, and execute high-impact design and build initiatives.

• Lead AI Economics Engineering: Architect cost models, metering systems, telemetry, and adaptive routing policies that balance model accuracy, latency, and operational spend across the engineering organization.

• Drive Cross-Group Initiatives: Plan and technically lead initiatives spanning multiple engineering teams; establish shared interfaces and platform contracts with Autonomous Coding, CI/CD pipelines, and Code Factory.

• Resolve Architectural Deficiencies: Identify and remediate root causes of complex architectural bottlenecks (latency, throughput, state management, dependencies) across distributed systems.

• Evaluate Build-vs-Buy Choices: Continuously assess emerging AI tooling and foundational models, recommending vendor-neutral, future-proof integration patterns.

• Represent Group Architecture: Lead department-level technical planning, establish architectural RFC standards, and facilitate rigorous design reviews across product areas.

• Raise Operational Excellence: Set production standards for resilience, testing, and deployment; act as a lead incident resolver capable of coordinating responses to high-severity incidents and driving post-incident reviews to root-cause prevention.

• Mentor & Elevate Talent: Actively coach and develop Senior (IC3) and Staff (IC4) engineers, cultivating an engineering culture of craft, ownership, and psychological safety.

What you’ll need:

• Education & Minimum Experience Requirements: Bachelor’s Degree + 4+ Years of Experience OR Master’s Degree + 3+ Years of Experience in software engineering, computer science, or a related technical field.

• Proven track record of technical leadership on software initiatives spanning multiple teams and complex distributed architectures.

• Adept system design capability with large-scale, high-availability distributed systems, platform infrastructure, and cross-domain APIs.

• Hands-on engineering experience building with LLM-based architectures, model APIs, and AI-assisted development tools (coding agents, developer harnesses, prompt/context evaluation, tool integration).

• Hands-on experience designing or operating model evaluation pipelines, AI proxies/gateways, or dynamic routing systems.

• Demonstrated ability to analyze infrastructure unit economics, capacity trade-offs, and operational telemetry.

• Exceptional communication and cross-functional leadership skills, with a track record of driving technical alignment across engineering squads and leadership.

• Commitment to engineering best practices, security guardrails, data privacy, and maintainable software design.

AI-Assisted Engineering Expectations:

• Use AI tools responsibly to accelerate prototyping, explore new architectures, and streamline ramp-up across new domains.

• Review AI-generated code and architecture critically, enforcing rigorous automated testing, safety, and long-term maintainability.

• Adhere strictly to data-handling and security protocols to safeguard proprietary and member data.

• Elevate team productivity by sharing effective AI development workflows, spec templates, and evaluation guardrails.

Nice to have:

• Experience designing or scaling internal developer platforms (IDPs) and developer tooling at enterprise scale.

• Practical exposure to FinOps frameworks for tracking and optimizing cloud or AI compute spend.

• Direct experience developing autonomous agentic workflows or deep integrations into engineering development lifecycle tools.

• Background in financial technology, banking platforms, or regulated engineering environments.