The CompanyRational Dynamics builds customized AI reasoning systems for high-cognitive-complexity work, beginning with institutional finance.Our initial market is the world’s leading institutional asset owners. We work very closely with these customers to create specialized, rigorous benchmark datasets encompassing their most valuable and difficult knowledge work. Then we use the benchmarks to construct agentic large reasoning models, applying the same rigor to prove that the models correctly do the work. Customers access the models through a tailored application service, making their most skilled, expensive workers dramatically more productive.We are an early-stage startup. Our founders previously started Voleon, now one of the world’s largest systematic investment managers, and recognized as a longstanding industry leader in applied machine learning. They bring to Rational Dynamics the same research discipline and data-driven focus that succeeded in the unforgiving, high-stakes setting of financial markets.Job DescriptionWe are hiring a Senior Manager of Engineering to lead a multidisciplinary team of engineers and scientists building agentic AI systems that work in real enterprise environments.This is not a pure people-management role. The right person thinks like a founder: they care about customers, product, technical architecture, velocity, team health, and code in the same week. You should have been hands-on in agentic development and want to stay close to the work while leading a substantial team.You will manage engineers and scientists building systems that combine LLMs, retrieval, agent orchestration, evaluation, data pipelines, customer-specific workflows, and enterprise deployment constraints. You will help turn early customer needs and feedback into reliable, reusable platform capabilities while keeping the team focused on speed, rigor, and customer delight.ResponsibilitiesLead, coach, and scale a high-performing team of engineers and scientists; initially as a line manager, with scope to manage managers as the organization growsOwn delivery of agentic AI systems from ambiguous customer need through prototype, production deployment, evaluation, and iterationStay technically hands-on through architecture reviews, build/buy decisions, agentic workflow design, eval strategy, and urgent customer-critical problem solvingPartner with the Director of Product, Director of UX, and customer-facing teams to translate customer workflows into clear technical roadmapsBuild operating mechanisms that help the team move fast without unnecessary process: crisp priorities, clear ownership, fast feedback loops, and disciplined executionRaise the engineering bar for reliability, observability, security, compliance, and deployment quality in high-consequence enterprise environmentsRecruit, develop, and retain exceptional technical talent; create a culture where engineers and scientists do their best workModel RD’s tenets: continuously delight customers, remove bottlenecks, disagree and commit, take ownership of every problem, prototype rapidly, and stay at the leading edgeRequirementsSignificant experience leading engineering teams that ship production software in complex, ambiguous environmentsDemonstrated ability to manage strong technical ICs, including engineers and/or applied scientistsHands-on experience building with modern AI systems, such as: agents, RAG, tool use, workflow orchestration, evaluations, LLM applications, or adjacent systemsStrong product and customer judgment: you can identify what customers truly need, not just what they initially ask forEnterprise-grade engineering instincts, including security, data boundaries, observability, deployment, and operational reliabilityFounder-like ownership: high agency, low ego, bias for action, comfort with ambiguity, and willingness to take on whatever matters mostClear communication and strong judgment under pressure; able to debate hard, align quickly, and executePreferred QualificationsExperience at an early-stage startup or as an early technical leader scaling a product from 0→1 or 1→NExperience managing managers or building the structure for a growing engineering organizationExperience with enterprise customers in regulated or high-consequence industries such as finance, healthcare, defense, or infrastructureExperience leading teams that combine research, applied ML, infrastructure, and product engineeringFamiliarity with customer-deployed systems, multi-cloud or customer-cloud environments, security reviews, and compliance requirementsWhy this role mattersRD’s success depends on turning frontier AI capability into systems customers trust for their most important work. This role sits at the center of that effort: building the team, shaping the architecture, staying close to the code, and making sure customer value compounds into a durable platform.
