We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Engineering Leader at The Voleon Group. Remote Location: Remote, United States. About Us. Rational Dynamics builds customized AI reasoning systems for high-cognitive-complexity work, beginning with institutional finance. We 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.. What you’ll do. Lead, coach, and scale a high-performing team of engineers and scientists; initially as a line manager, with scope to manage managers as the organization grows.. Own delivery of agentic AI systems from ambiguous customer need through prototype, production deployment, evaluation, and iteration.. Stay technically hands-on through architecture reviews, build/buy decisions, agentic workflow design, eval strategy, and urgent customer-critical problem solving.. Partner with the Director of Product, Director of UX, and customer-facing teams to translate customer workflows into clear technical roadmaps.. Build operating mechanisms that help the team move fast without unnecessary process: crisp priorities, clear ownership, fast feedback loops, and disciplined execution.. Raise the engineering bar for reliability, observability, security, compliance, and deployment quality in high-consequence enterprise environments.. Recruit, develop, and retain exceptional technical talent; create a culture where engineers and scientists do their best work.. Model RD’s tenets: continuously delight customers, remove bottlenecks, disagree and commit, take ownership of every problem, prototype rapidly, and stay at the leading edge.. What we’re looking for. Significant experience leading engineering teams that ship production software in complex, ambiguous environments.. Demonstrated ability to manage strong technical ICs, including engineers and/or applied scientists.. Hands-on experience building with modern AI systems, such as: agents, RAG, tool use, workflow orchestration, evaluations, LLM applications, or adjacent systems.. Strong product and customer judgment: you can identify what customers truly need, not just what they initially ask for.. Enterprise-grade engineering instincts, including security, data boundaries, observability, deployment, and operational reliability.. Founder-like ownership: high agency, low ego, bias for action, comfort with ambiguity, and willingness to take on whatever matters most.. Clear communication and strong judgment under pressure; able to debate hard, align quickly, and execute.. Preferred. Experience at an early-stage startup or as an early technical leader scaling a product from 0→1 or 1→N.. Experience managing managers or building the structure for a growing engineering organization.. Experience with enterprise customers in regulated or high-consequence industries such as finance, healthcare, defense, or infrastructure.. Experience leading teams that combine research, applied ML, infrastructure, and product engineering.. Familiarity with customer-deployed systems, multi-cloud or customer-cloud environments, security reviews, and compliance requirements.. Why this role matters. RD’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.