Engineering Manager, AI – Agentic Enablement

This is a fully remote position, open to applicants in Hong Kong, +4 more countries.

📋 Description

• Lead engineering initiatives to transform AI into a production capability across Reap.

• Oversee the AI platform layer, which includes MCP servers, agentic workflows, internal AI infrastructure, and enablement.

• Establish technical direction and engage in code and design reviews.

• Collaborate with teams across Engineering, Operations, Compliance, Finance, and Support.

• Manage the design, security framework, and roadmap of the agentic data layer.

• Define standards for authentication, permissions, rate limits, auditing, and security for MCP servers and tools used by agents.

• Broaden agentic data coverage encompassing cards, payments, treasury, onboarding, compliance, and support.

• Develop evaluation and observability systems to assess answer quality, tool-call accuracy, latency, and failure modes.

• Revamp operational workflows to ensure agents implement SOPs with human approval checkpoints.

• Convert SOPs and operational challenges into structured agentic workflows.

• Create features for auditability, including error handling, retries, rollback, audit trails, and escalation processes.

• Manage internal AI infrastructure for shared model access, handling of secrets and data, deployment pathways, and secure hosting.

• Provide support for teams developing AI-enabled internal dashboards and tools.

• Implement AI governance, risk classification, data-flow documentation, access controls, and production logging.

• Set standards for handling customer PII and regulated data in cooperation with Security, Compliance, and Legal teams.

• Enhance engineering AI fluency through improved skills, workflows, tooling, and documentation.

• Recruit, develop, and lead a small, senior team.

• Measure impact through reduced review times, increased throughput, shorter cycle times, and improved capacity.

⛳️ Requirements

• Minimum of 8 years of experience in software engineering.

• At least 2 years in a technical leadership or management position.

• Proven track record in designing, deploying, and promoting the adoption of AI or agentic systems in production settings.

• Hands-on expertise with Claude and other LLM APIs, AWS Bedrock, MCP or similar agent-tooling layers, Python or TypeScript orchestration, and workflow engines like n8n.

• In-depth knowledge of LLM failure modes, including hallucination, tool misuse, prompt injection, and silent degradation.

• Strong systems thinking with the capability to progress from discovery to optimization without depending on external consultants.

• Ability to collaborate directly with non-technical operators and transform workflows into viable systems.

• Sound judgment regarding data classification, access control, and audit requirements within a regulated financial context.

• High standards for code quality, reliability, and peer review processes.

• Excellent communication skills and a respectful approach to challenging ideas.

• Nice to have: experience with MCP servers, agent tooling layers, or LLM gateways at a production scale.

• Nice to have: background in payments, cards, fintech, or another regulated financial sector.

• Nice to have: familiarity with AML/KYC, fraud, or reconciliation workflows.

• Nice to have: experience in deploying automation within a SOX-regulated or equivalent compliance environment.

• Nice to have: experience with internal platforms or developer experience.

• Nice to have: experience conducting security reviews or establishing paved-road deployment paths.

• Nice to have: familiarity with LLM evaluation, tracing, and observability tools such as LangSmith, Braintrust, or OpenTelemetry.

• Nice to have: experience leading teams in high-growth settings.

• Nice to have: experience in building an AI enablement, automation, or internal platform function from the ground up.

• Main stack includes: TypeScript, Node.js, NestJS, and AWS.

🏝️ Benefits

• Flexible hybrid or remote work environment with a global, collaborative team.

• Insurance coverage available after the probation period.

• Reap Card stipend.

• Access to AI tools for work purposes.

• Opportunities to learn, experiment, and grow with AI technologies.

• A culture that promotes innovation, inclusion, and continuous learning.