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About the Role

Chime is seeking a Staff Software Engineer to lead the technical direction for building member-facing AI experiences using LLMs. This role involves architecting agent systems, evaluation frameworks, and guardrails to ensure reliable, safe, and scalable AI delivery to millions of members. You will be hands-on in designing new capabilities, prototyping, shipping production code, and improving team standards. The position requires strong engineering fundamentals and a product-oriented approach, managing capabilities from conception to measurement and iteration.

Responsibilities

Set the technical direction and architecture for how Chime builds with LLMs on Jade: the agent architectures, prompt strategies, and orchestration patterns that shape how Jade reasons and acts, and that other engineers build on
Design, build, and scale new member-facing capabilities for Jade, from prototype through production, moving fluidly between product discovery and hands-on engineering
Build the eval frameworks, observability, and guardrail systems that let the team ship LLM-powered features with speed, safety, and confidence
Develop and harden the backend services and internal tooling behind Jade (model routing, prompt management, agent orchestration, and evaluation pipelines), improving reliability and performance as we scale
Leverage AI and LLMs natively in your own workflow, using AI-assisted coding and rapid prototyping, and turn one-off AI workflows into reusable systems (agent loops, evals, custom tooling) that compound the whole team's output
Champion AI-native development practices across the team: set the quality gates that keep AI-assisted output production-ready, encode recurring failure modes into shared evals and guardrails, and push the team to work at the frontier of what AI tooling makes possible
Exercise judgment about where and how AI is applied, deciding which problems get an AI-generated first pass and which need human judgment, and calibrating model autonomy to the stakes and reversibility of each decision
Drive experimentation and rapid iteration: design A/B tests, analyze results, and make data-informed decisions about what to scale, pivot, or kill
Partner cross-functionally with product, design, data science, and risk to understand member pain points and deliver secure, scalable solutions
Contribute to technical design and uphold high standards across the codebase through code reviews and mentorship, multiplying the impact of the engineers around you
Participate in on-call rotation; being on call may include responding to incidents outside of regular working hours when necessary

Requirements

8+ years of backend or full-stack software development experience in production environments
Deep expertise in system design, distributed systems, and architectural patterns for high-scale systems
Proficiency with Python or comparable frameworks, with the breadth to make sound decisions across the stack
AI-native fluency: you actively build with LLMs, AI code assistants, and generative AI tooling as a daily part of your workflow, not as a side project
Hands-on experience building or shipping LLM-powered product features (agents, conversation experiences, evals, prompt strategies, or guardrails) at production scale
A track record of turning AI into durable leverage: reusing and improving workflows, encoding recurring fixes into evals, rules, and tooling instead of solving the same problem twice, and acting as the first and most critical reviewer of AI-generated output
Sound judgment about where and how to apply AI, calibrating verification effort and model autonomy to the stakes, reversibility, and cost of each task
Experience with transactional databases (e.g., Postgres) and caching systems (e.g., Redis), and a strong focus on writing maintainable, well-tested code
Demonstrated technical leadership across teams: setting direction, driving architectural decisions, and aligning cross-functional stakeholders without relying on positional authority
A track record of mentoring engineers and raising the technical bar
A product mindset with a bias toward action: you ship v1 fast, learn from real usage, and iterate, letting data settle debates

Skills

Python
System Design
Distributed Systems
LLMs
AI Code Assistants
Generative AI Tooling
Transactional Databases
Postgres
Redis
Agent Development
Fintech
Startup Environments

Location

Onsite

Work Type

Full-time
Hybrid

Experience Level

Staff
8+ years

Salary/Compensations

$223,000.00 - $308,000.00

Benefits

Bonus
Competitive equity package
Backup child, elder, and pet care
Subsidized commuter benefits
Comprehensive health, financial, and wellbeing benefits
Generous vacation policy
Company-wide paid days off
1% of time off to support local community organizations
Annual wellness stipend
Up to 22 weeks of paid parental leave for birthing parents
12 weeks of paid parental leave for non-birthing parents
Access to family planning reimbursement

About the Company

Chime is a financial technology company that believes everyone can achieve financial progress. They offer core banking services that are helpful, easy, and free, empowering millions to take control of their finances and work towards their goals. The company is driven by a team of problem solvers, dreamers, and builders obsessed with their members, operating with an owner's mindset and a commitment to integrity. Chime encourages boldness, big dreams, and risk-taking, fostering an entrepreneurial culture where employees are stewards of the mission to help everyday Americans achieve financial progress.

Equal Opportunity

Chime is proud to be an Equal Opportunity Employer. They consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis. They will also consider qualified applicants with criminal histories in a manner consistent with applicable laws. Accommodation is available for individuals with disabilities during the application process.