Location: San Francisco · On-site, five days a week

Department: Engineering

Employment type: Full time

Level: SWE II / Senior · Individual contributor

Compensation: $220,000–$260,000 annual base salary + equity

About interface.ai

Our mission is to make intelligent, personalized financial services accessible to everyone. interface.ai builds AI agents for the banks and credit unions that serve everyday Americans, helping financial institutions deliver better service and making it easier for people to get the support they need.

More than 100 banks and credit unions use interface.ai, reaching over 10 million people. With $30M in Series A funding and a cash-flow-positive business, we're building toward an AI-powered contact center and a banking experience designed around intelligent agents. Our ambition is to help millions of people navigate their financial lives with greater confidence.

We're bringing that same ambition to how our company works: equipping every team with AI that helps people accomplish more, focus on meaningful work, and serve our customers better.

The Role

As our Applied AI Engineer, Business Automation, you'll build the systems that make every team at interface.ai more productive. Work across engineering, product, sales, marketing, customer success, finance, operations, and talent to understand how work gets done, identify the highest-impact opportunities, and turn recurring business processes into reliable AI-powered workflows.

You'll own our in-house business automation platform: the shared foundation that connects the best available AI tools, agents, company knowledge, and business systems to take work from request to completed outcome. Build on existing internal tools and develop reusable capabilities that each team can adapt to its own work. Evaluate what to build, buy, or integrate based on quality, reliability, cost, and employee experience.

This is a dedicated, hands-on engineering role with the company itself as your customer. You'll work directly with CEO Srinivas Njay, partner with CTO and Co-Founder Bruce Kim, and embed with teams to learn their domain-specific rules, exceptions, and decisions. Own the full journey from discovering a workflow to shipping it, helping employees adopt it, and improving it in production. Your goal is to make AI a dependable part of daily work in every department, with measurable gains in employee productivity.

What You'll Own

Workflow discovery and prioritization. Work alongside employees and team leaders to map recurring work, bottlenecks, handoffs, and exceptions. Establish baselines and prioritize a focused roadmap by time saved, quality improved, business impact, and implementation effort.

The business automation platform. Build and evolve shared integrations, knowledge access, agent orchestration, and employee-facing tools. Make successful automations reusable across teams while supporting each function's distinct processes and requirements.

Automation from start to finish. Connect intake, context gathering, execution, approvals, updates to business systems, and follow-through. Deliver workflows such as customer handoffs, account research, reporting, onboarding, and recruiting operations that reach a verifiable outcome.

Domain-specific judgment. Learn what a good result means in each department. Translate business rules, terminology, data dependencies, and edge cases into workflow logic and evaluations, with clear human review where judgment or authorization is needed.

The right tools for the job. Continuously evaluate frontier models, agent frameworks, automation platforms, and SaaS capabilities. Combine the best available tools with custom engineering, and evolve the stack as capabilities improve.

Production quality and ownership. Own architecture, APIs, data models, prompts, evaluations, deployment, and ongoing maintenance. Build in appropriate access controls, auditability, monitoring, retries, and recovery so employees can trust the systems they use.

Adoption and measurable results. Pilot with teams, train users, document workflows, and improve from feedback. Help colleagues use shared tools and templates to improve their own work. Track adoption, hours saved, cycle time, error rates, output quality, and operating cost; use those results to decide what to expand next.