
Leading company in the software industry
Manager, Software Engineering (AI Platform Engineering )
At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.
If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.
GTreasury, now a Ripple solution, was acquired by Ripple in 2025, marking a significant expansion into the multi-trillion-dollar corporate finance arena.
GTreasury has more than 40 years of experience supporting some of the world’s largest and most sophisticated companies. Integrating its treasury command center into Ripple’s technology stack gives corporates the ability to move, manage and optimize liquidity in real-time, across traditional and digital assets, under one expanded umbrella.
Join us to build the future of corporate treasury and the infrastructure that powers the Internet of Value.
The Opportunity
The GSmart AI platform is Ripple Treasury's production AI middleware layer — the infrastructure that enables generative AI capabilities across the entire product suite. As Manager of AI Platform Engineering, you will own this platform end-to-end: building new AI inference endpoints, writing prompts and evaluations, and expanding generative AI integration into solution areas that haven't previously used AI. You will also build and lead a team of up to four engineers.
This is a hands-on leadership role where you will write code and ship features alongside your team while defining the technical direction of AI across Ripple Treasury. The outputs of your platform reach CFOs and treasurers at major global banks — accuracy, reliability, and trust are non-negotiable.
What You'll Do
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Own the GSmart AI platform — design, build, operate, and evolve the production AI middleware serving enterprise treasury clients, including inference endpoints, prompt pipelines, and context engineering architecture.
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Build and lead a high-performing team of up to four AI platform engineers, coaching direct reports, managing performance, and fostering a culture of engineering rigor.
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Write and maintain production prompts using context engineering principles — structured prompt design and data transformation rather than retrieval-augmented generation.
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Build evaluation frameworks as first-class engineering — create eval rubrics, golden datasets, LLM-as-a-judge pipelines, and CI/CD-integrated quality gates for every AI feature.
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Partner with authorities across treasury domains (cash forecasting, payments, risk management) to understand business logic and build domain-accurate evaluations.
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Advocate for generative AI adoption across Ripple Treasury solution areas, educating product and engineering teams on what AI can and cannot do in regulated financial contexts.
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Operate and maintain cloud infrastructure — Azure Container Apps, API Management, Key Vault, Redis, and Langfuse observability for the AI platform.
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Ensure compliance with AI governance frameworks relevant to regulated financial services, including ISO/IEC 42001, EU AI Act, and SWIFT CSCF.
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Drive AI-assisted engineering practices — champion daily use of AI coding tools (Claude Code, Copilot, Cursor) across the team and broader engineering organization.
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Recruit exceptional engineers — partner with talent acquisition to identify, interview, and hire AI platform engineers as you scale the team.
What You Bring
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7+ years of software engineering experience with at least 2 years building and operating AI/ML systems in production environments (not prototypes or demos)
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2+ years of engineering management experience, including hiring, coaching, and growing engineers
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Hands-on experience with LLM-based systems in production — prompt engineering, inference optimization, and production monitoring at scale
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Strong evaluation engineering skills — experience building golden datasets, eval rubrics, or automated evaluation pipelines for AI system quality
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Cloud infrastructure expertise — experience deploying and operating containerized services on Azure (or equivalent cloud), including CI/CD pipelines
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Proficiency in Python for AI workflows (agentic flows, context engineering, data transformation) and familiarity with .NET backend systems
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Experience collaborating with domain experts to translate business knowledge into AI system design and evaluation criteria
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Excellent communication skills — ability to explain AI capabilities and limitations to non-technical partners in clear, concrete terms
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Comfort working in regulated environments where outputs must be accurate, auditable, and trustworthy
Nice to Have
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Experience with the specific tech stack: Azure OpenAI (GPT-4.1), LiteLLM proxy, Langfuse, Azure Container Apps, Redis
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Familiarity with AI governance frameworks (ISO/IEC 42001, EU AI Act, NIST AI RMF) or model risk management practices
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Background in financial services, treasury, or enterprise SaaS
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Experience building context engineering architectures (as distinct from RAG)
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Contributions to AI evaluation tooling or open-source AI infrastructure projects
WHO WE ARE:
Do Your Best Work:
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The opportunity to build in a fast-paced start-up environment with experienced industry leaders
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A learning environment where you can dive deep into the latest technologies and make an impact. A professional development budget to support other modes of learning.
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Thrive in an environment where no matter what race, ethnicity, gender, origin, or culture they identify with, every employee is a respected, valued, and empowered part of the team.
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In-office collaboration for moments that matter is important to our culture, and we give managers and teams the flexibility to decide which 10+ days a month they come in.
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Bi-weekly all-company meeting - business updates and ask me anything style discussion with our Leadership Team
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We come together for moments that matter which include team offsites, team bonding activities, happy hours and more!
Take Control of Your Finances:
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Competitive salary, bonuses, and equity
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Competitive benefits that cover physical and mental healthcare, retirement, family forming, and family support
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Employee giving match
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Mobile phone stipend
Take Care of Yourself:
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R&R days so you can rest and recharge
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Generous wellness reimbursement and weekly onsite & virtual programming
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Generous vacation policy - work with your manager to take time off when you need it
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Industry-leading parental leave policies. Family planning benefits.
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Catered lunches, fully-stocked kitchens with premium snacks/beverages, and plenty of fun events
*Benefits listed above are for full-time employees. *
Ripple is an Equal Opportunity Employer. We’re committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.
Please find our UK/EU Applicant Privacy Notice and our California Applicant Privacy Notice for reference.
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关于Ripple

Ripple
Series CRipple is an American technology company which offers enterprise blockchain products on the XRP Ledger and other networks. Originally named OpenCoin and renamed in 2015, the company was founded in 2012 and is based in San Francisco, California.
501-1,000
员工数
San Francisco
总部位置
$10B
企业估值
评价
2条评价
2.9
2条评价
工作生活平衡
2.5
薪酬
3.5
企业文化
2.0
职业发展
3.5
管理层
2.5
25%
推荐率
优点
Potential for promotions
Higher pay opportunities
Implementation management role
缺点
Poor team dynamics
Colleague resentment issues
Work-life balance concerns
薪资范围
60个数据点
Senior/L5
Staff/L6
Staff
Director
Senior/L5 · Senior Security Engineer
1份报告
$279,500
年薪总额
基本工资
$215,000
股票
-
奖金
-
$279,500
$279,500
面试评价
3条评价
难度
3.0
/ 5
时长
14-28周
面试流程
1
Application Review
2
Technical Screen
3
Virtual Onsite
4
Team Matching
5
Offer
常见问题
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Past Experience
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