[Remote] Manager, AI Engineering - AI & Business Tech Engineering

Note: The job is a remote job and is open to candidates in USA. DigitalOcean is a cutting-edge technology company focused on simplifying cloud and AI for builders. They are seeking a Manager, AI Engineering who will lead a team to deliver AI-native capabilities and transform the company's operations with AI at its core.ResponsibilitiesLead, mentor, and grow a distributed team of AI engineers (starting from an established nucleus, scaling to a high-performing group of 6-8) building copilots, agents, and the internal AI platform that powers themAct as a player-coach: review architecture, contribute to design and prototypes for critical agents and platform components, write code where the team's leverage demands it, and set a high technical barShape and execute the technical roadmap for the AI Engineering team in partnership with the Senior Director, AI & Business Technology Engineering-across internal AI copilots for teams, the AI platform and developer experience that supports them, and AI-native business process re-engineering across DigitalOceanDesign and deliver agentic systems end to end: orchestration, tool use, capability boundaries, memory and state, evaluation, observability, runtime governance, and incident response for non-deterministic systemsBuild and evolve our internal AI platform-including the MCP gateway, agent runtimes, model access and routing, evaluation harnesses, and self-service developer experience-so every DO engineer and business team has a paved path to building with AI safelyPartner with leaders from Finance & Supply Chain Systems, People Systems, Sales & Marketing Systems, Collaboration & Security Systems and their non-engineering business owners to identify the highest-leverage AI opportunities and ship themCollaborate closely with peer leaders in Enterprise Architecture, Data Engineering, Program Management, and Security to ensure our AI systems are well-architected, governed, observable, and trustedChampion modern AI engineering practices: evaluation-first development, prompt and agent versioning, runtime guardrails, audit logging, human-in-the-loop escalation, and cost attribution for LLM workloadsDevelop OKRs for the team, instrument the right business and engineering metrics, and clearly report progress to leadership and the broader organizationRecruit world-class AI engineering talent in Boston, Cambridge, and broader US & non-US hubs; coach and develop the team you build; create an environment where engineers do the best work of their careersContribute to AI & Business Technology Engineering leadership team planning and goal-setting, represent the AI Engineering team's perspective in cross-org forums, and contribute back to internal communities of practice (agent-skills, Claude pilot, AI workflows)SkillsSignificant experience as a software engineering manager, with a strong track record of leading and growing engineering teams that ship reliably in productionHands-on engineering depth in modern AI/ML systems: large language models, retrieval-augmented generation, agents and tool use, evaluation, and the operational discipline of LLMOps (prompt versioning, regression testing, cost attribution, observability for non-deterministic outputs)Practical experience building or operating agentic systems-orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or equivalents), Model Context Protocol (MCP) tooling, vector stores, and runtime guardrailsExperience designing internal developer platforms or productivity tooling that engineers actually choose to adopt, including golden paths, self-service APIs, and SDKsA clear point of view on AI governance and safety: audit logging, capability boundaries, minimum-privilege tool access, human-in-the-loop escalation, and alignment with frameworks like the NIST AI RMFStrong software engineering fundamentals in at least one production language (Python, Go, TypeScript, or Java) and modern cloud-native infrastructure (Kubernetes, serverless, gRPC, observability stacks)A bias for shipping: integrating customer and stakeholder feedback into how the team works, focusing on outcomes over outputs, and unblocking the team with pragmatic decisionsExcellent written and verbal communication skills, with a demonstrated ability to influence non-engineering stakeholders and translate ambiguous business problems into well-scoped AI systemsExperience hiring and retaining strong AI engineering talent in competitive markets, and growing junior engineers into senior contributorsComfort working in a hybrid environment-able to partner closely with our Boston/Cambridge community while leading distributed teammates across the US and beyondBonus: experience re-engineering business processes in enterprise systems (Workday, Salesforce, NetSuite, Greenhouse, or similar), or working closely with finance, people, GTM, or support functions on AI deploymentsBonus: prior experience deploying AI tooling at scale to internal users (Cursor, Claude Code, GitHub Copilot, or equivalent enterprise rollouts)BenefitsWe provide employees with reimbursement for relevant conferences, training, and education.All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.Employee Assistance ProgramLocal Employee MeetupsFlexible time off policyYou may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance.We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.Company OverviewDice is the go-to career marketplace for tech professionals. It was founded in 2010, and is headquartered in Drachten, Friesland, NLD, with a workforce of 201-500 employees. Its website is https://www.or-quest.nl/.Company H1B SponsorshipDice has a track record of offering H1B sponsorships, with 2 in 2022, 4 in 2021, 5 in 2020. Please note that this does not guarantee sponsorship for this specific role.