R&D Engineering Manager, AI Evaluation

About Us Resaro was founded on the belief that AI will change the world in ways we cannot even imagine - but every new technology needs safeguards to advance. We are an independent, third-party AI assurance company: we build the software and run the evaluations that let enterprises and public-sector bodies deploy AI they can actually trust. Our work spans computer vision, generative AI and LLMs, vision-language models, and increasingly agentic and autonomous systems, for clients across government, defence, and commercial sectors. Our product, the Approved Intelligence Platform (AIP), is where this becomes real software: customers upload datasets, register the AI systems they want tested, run rigorous evaluations, and produce defensible evidence and reports. We're hiring a team player-coach to lead the core AIP evaluation engine team - a senior engineer who still builds, and who leads, grows, and line-manages the engineers building it. You'll partner closely with the Product team, which owns the roadmap and requirements; you own execution, technical strategy, engineering quality, and the people. This role can be based either in Singapore or Munich. What You'll Do Lead the technical direction of our AIP evaluation engine across verticals: computer vision, LLM/RAG, VLM, and emerging areas like agentic and embodied AI systems. Stay hands-on where it matters most e.g. spikes and hotspot architecture: You review your team's code and set the bar for engineering quality. Own conceptual integrity as the system grows: drive the spike-to-ADR discipline, keep architectural decisions coherent, and prevent uncontrolled coupling on key hotspots. Line-manage your team: 1:1s, growth, performance, and career development for a team of 5–10 engineers and scientists across Singapore and Europe, and partner on hiring to raise the team's bench strength. Own delivery and engineering quality: translate the roadmap into executable plans, sequence epics, and drive down incident-rate-per-run and median defect-resolution time against quarterly baselines Manage the defect flow: prioritise reported defects and bugs, lead deep-dive problem-solving to pre-empt future incidents, and improve delivering on committed roadmaps. Build a strong multi-disciplinary team: create the shared context and ways of working that let engineers, AI engineers, and governance analysts collaborate on epics without constant top-down orchestration. Partner across teams: this role reports to the CTO and works closely with the Product team to communicate loads and dependencies, and manage scoping and resourcing to ensure consistent execution against the product roadmap. What We're Looking For 7+ years of professional software engineering experience shipping and operating production systems, including time as a tech lead and/or engineering manager. Direct people-management experience (or clear, evidenced readiness for it) - this role formally line-manages the engineers, and growing people is a core part of the job. Proficiency in Python for backend services and data pipelines. Demonstrated technical leadership of a small engineering team - owning architecture decisions and setting engineering standards. Strong architecture judgement - experience managing coupling, leading migrations, and keeping a growing system coherent e.g. through ADRs and dependency hygiene. A genuine bias to stay hands-on while leading - you find satisfaction in both shipping code (on the hard problems) and growing people. Clear written and verbal communication, and comfort being measured against concrete quarterly outcomes - including across a distributed, Singapore–Europe team. Nice To Have Exposure to data-quality tooling for, or integration/evaluation/testing/assurance across, one or more AI domain areas: LLM/RAG, agentic systems, computer vision. Familiarity with a typed frontend stack (TypeScript/React) - although not core responsibility the team occasionally touches some UI surfaces. Data-intensive pipelines with columnar/lakehouse formats (Parquet/Iceberg) and DuckDB or similar. Container-based or serverless execution frameworks (Nuclio or comparable function/orchestration systems). Kubernetes and Helm for production workloads. GPU/CUDA infrastructure for model inference at scale. Leading a platform migration with live, enterprise customers where evidence, auditability, and back-compatibility matter. Our Hiring Blueprint We hire to a high, transparent bar. We look for: Production-grade code. You ship software that is correct, tested, observable, and maintainable by others Communication and handover. You write clearly, document decisions, and leave work in a state another engineer can pick up. As a lead, you make your team's context legible. Independent operation. You can take an ambiguous problem, scope it, decompose it, sequence it, and drive it to a shipped outcome without close supervision - and you help your team do the same. T-shaped profile. Deep in your core domain (AI/backend/systems/etc.) and broad enough to operate steadily across the stack and the ML-evaluation domain Resaro is an Equal Opportunity Employer. We respect each individual and support the diverse cultures, perspectives, skills and experiences within our teams.