Engineering Manager, AI (Agentic Enablement)

About Reap

Reap is a fintech company based in Hong Kong, operating globally with employees in various countries. The company facilitates financial connectivity worldwide by integrating traditional finance with stablecoin technology, enabling smoother monetary transactions. Their offerings include stablecoin-powered corporate cards, payment solutions, and expense management systems that simplify financial operations and aid business growth. Their APIs allow embedding stablecoin-based finance into third-party products ranging from Visa card issuance to cross-border payments.

Supported by prominent investors such as Acorn Pacific, Index Ventures, and HashKey Capital, Reap is pioneering seamless, stablecoin-enabled finance without borders.

Role Overview

Reap operates regulated multi-jurisdictional card and payment services, involving numerous operational tasks like onboarding, KYB reviews, compliance checks, fraud investigations, and customer support, all governed by documented SOPs. The company is transitioning these processes into AI-native workflows, embedding AI into operations to automate SOP execution with human oversight where necessary. Teams are increasingly incorporating AI into internal dashboards and development processes.

The Engineering Manager, AI role is pivotal in institutionalizing AI as a core engineering discipline with clearly defined ownership, architecture, governance, and team leadership.

Key Responsibilities

• Lead the engineering efforts advancing AI production capabilities at Reap, overseeing the AI platform layer including MCP servers, agentic workflows, internal AI infrastructure, and enabling other teams to build safely on this foundation.
• Design, secure, and roadmap the agentic data layer, managing access controls, authentication, permissioning, rate-limiting, and auditing to ensure safe handling of live business and financial data.
• Extend agentic data coverage across multiple domains like cards, payments, treasury, onboarding, compliance, and support, maintaining consistency and reliability of agent-facing tools.
• Develop evaluation and observability mechanisms to monitor quality, correctness, latency, and failure modes of AI responses and take corrective measures.
• Revamp operational workflows to maximize agentic system execution of SOPs with human approval gates at critical points, collaborating closely with Compliance, Operations, Finance, and Support.
• Promote an "agentic first" mindset by creating tools and enablers that encourage quick and safe adoption of AI workflows.
• Focus on designing audit-friendly workflows with robust error handling, retries, rollbacks, structured audit logs, and clear escalation paths compliant with regulatory requirements.
• Prioritize AI automation projects based on operational leverage and risk assessment, refusing to automate processes lacking safety guarantees.
• Manage the internal AI platform infrastructure, including model access, secure data and secrets management, deployment pipelines, and hosting environments, ensuring secure and efficient service.
• Support other teams developing AI-powered dashboards and tools by providing robust frameworks, pragmatic security reviews, and launch assistance without compromising standards.
• Establish governance processes that balance compliance with developer velocity, making the compliant approach the preferred path by minimizing friction.
• Classify projects by risk tier upfront, ensuring production releases have designated owners, documented data handling, access controls, and proper logging.
• Define standards for managing customer PII and regulated data in AI systems, working closely with Security, Compliance, and Legal teams across jurisdictions.
• Enhance AI literacy across the engineering organization by building skills, workflows, tooling, and documentation that improve developer experience and delivery speed.
• Run enablement processes like product management by tracking adoption, impact, and iterating on relevant tools while deprecating ineffective ones.
• Lead hiring, mentoring, and managing a small, experienced engineering team, guiding them to deliver high-impact AI solutions with accountability and technical excellence.
• Report measurable impacts on operations such as reductions in manual review times, increased throughput, shortened cycle times, and increased capacity for higher-judgment work.

Candidate Profile

• Minimum 8 years software engineering experience, including at least 2 years in technical leadership or management.
• Proven record of designing, deploying, and driving real-world AI or agentic system production adoption beyond experimental or demo stages.
• Expertise with modern AI technologies including Claude and similar LLM APIs, AWS Bedrock, MCP or equivalent agent tools, Python or TypeScript orchestration, and workflow engines like n8n.
• In-depth knowledge of LLM challenges such as hallucinations, tool misuse, prompt injections, and degradation, with ability to implement evaluation methods, safeguards, and human-in-the-loop controls.
• Strong systems thinking skills to independently carry projects from concept through design, development, deployment, and optimization.
• Capability to engage closely with non-technical stakeholders, comprehend operational workflows, and translate them into implementable solutions.
• Sound judgment on data classification, access management, and audit requirements within regulated financial settings.
• High standards for code quality, reliability, peer review, and collaborative development practices.
• Excellent communication skills, openness to constructive challenge, and fostering elevated team standards.
• Proficiency in TypeScript, Node.js, NestJS, and AWS is preferred but strong engineering fundamentals take precedence.

Desirable Qualifications

• Experience constructing or managing MCP servers, agent tooling layers, or LLM gateways at production scale.
• Background in fintech domains such as payments, cards, AML/KYC, fraud prevention, or reconciliation processes.
• Experience deploying automation under SOX or equivalent strict regulatory compliance frameworks.
• History of building internal platforms focused on developer experience and widespread adoption.
• Capability to conduct security reviews for internal tools and establish streamlined secure deployment workflows.
• Familiarity with LLM evaluation and observability tools such as LangSmith, Braintrust, or OpenTelemetry.
• Leadership roles in fast-growing, high-velocity technical environments.
• Prior involvement in founding AI enablement, automation, or internal platform teams from inception.

Work Environment and Benefits

• Opportunity for high impact in a rapidly expanding fintech startup.
• Flexible hybrid and remote working arrangements within a globally connected team.
• Insurance coverage provided after completing probation.
• Reap Card stipend provided to employees.
• Access and encouragement to use AI technologies at work, fostering continuous learning and innovation.
• A culture focused on innovation, inclusivity, and ongoing professional development.

Additional Information

After applying, candidates should verify receipt of a confirmation email and check spam folders to ensure future communications are received properly.