• Define the product strategy and own the roadmap for a new platform that sits at the intersection of AI, containers, and developer experience. • Define the vision, roadmap, and success metrics for Docker’s AI & Agent Platform. • You will define the product from the ground up — writing the first specs, prototyping with engineering, validating with customers, and iterating rapidly based on what you learn. • Write requirements, work with engineering to scope and prioritize, ship iteratively, and measure outcomes. • Define how pieces of the agentic ecosystem fit together. • Ensure the platform serves the full range of people who need agents to succeed. • Define the developer experience. • Work cross-functionally to ensure coherent product experiences and go-to-market alignment. • Influence technical direction. • Engage directly with developers, enterprises, and partners.

• Identify and prioritize high-impact workflows for agentic AI automation across business domains • Design AI agents and multi-agent systems to automate and augment business processes • Collaborate with AI Engineering, Data Science, and Product teams to translate use cases into technical solutions • Define and implement guardrails for AI agents (accuracy thresholds, explainability, bias mitigation) • Partner with Change Management Lead on providing advise/consultation on pilot programs • Track and report on key success metrics: Productivity gains, Cycle time reduction, User adoption and satisfaction, Output quality and accuracy • Continuously refine agents based on feedback, data, and evolving business needs

Role Description As the Team Leader, Engineering for Rowan, you will lead the engineering team behind one of Rocket Money’s most ambitious product bets: building an agentic personal finance assistant that works over text message and, over time, potentially other surfaces too. This role owns the engineering craft, execution, and growth of the engineers on Rowan. This is a role for an engineering leader who is excited by and experienced in AI as an execution layer, not just a conversation layer. Rowan’s promise is not “can it answer the question?” The promise is “can it safely, accurately, and verifiably solve the problem?” That means the work sits at the intersection of: - LLM-powered conversation - Deterministic execution systems - Human-in-the-loop operations - Money movement constraints - Trust and safety - Consumer-grade product craft You will set technical direction for the engineering team in service of the Rowan strategy, partner with other functional leaders on Rowan’s roadmap, grow senior engineers, and stay close enough to the product and systems to know what is actually working. You will help the team decide when a task should be handled by AI, by programmatic behavior, by a human, or by a hybrid workflow. You will also help create the operating system for how Rowan’s engineers build: - How we evaluate quality - Recover from mistakes - Earn customer trust - Turn ambiguous AI capabilities into dependable product experiences This is a good fit for someone who likes hard, slightly messy problems; who can move with urgency without turning urgency into panic; and who believes the less glamorous parts of agentic products (orchestration, approvals, evals, observability, operational fallbacks, and recovery paths) are not overhead. They are the product. In this role, you'll: - Lead, develop, and grow the Rowan engineering team, setting a high bar for technical judgment, product quality, customer trust, and steady execution. - Partner with product leadership to translate Rowan’s strategy (be the agent that finishes the job) into engineering plans and shipped capabilities that create measurable customer value. - Stay close to the full Rowan experience: conversational interfaces, orchestration, memory, app surfaces, detection systems, operational rails, human escalation paths, and the safety models required to act on someone’s finances. - Help the team build agentic capabilities that do consistent, correct and reliable work end-to-end. - Drive projects to a conclusion by making decisions, clearing blockers, aligning stakeholders, and helping the team consistently ship high-quality work customers can feel. - Build the systems and habits that make AI work dependable: eval frameworks, observability, approvals, fallbacks, recovery paths, human-in-the-loop workflows, and clear ownership. - Partner closely with Product, Design, Data, Operations, Legal, Support, and Engineering leadership to help choose the highest-leverage bets, make crisp tradeoffs, and bring an engineering point of view to what Rowan should and should not take on. - Create a team environment where senior engineers can stretch across product, AI, systems, operations, and trust while doing some of the best work of their careers. - Hold regular 1:1s, deliver performance reviews, build individualized growth plans, and tailor your coaching to each person’s strengths, ambitions, and working style. - Help raise the product bar beyond chat toward proactive, rewarding, trustworthy experiences that make Rowan feel like one assistant everywhere. - Stay curious about the frontier of AI engineering and help the team adopt new workflows, tools, and patterns where they make the work better. Qualifications - Experience shipping production agentic software and a strong track record leading engineering teams, including senior ICs working in complex or ambiguous domains. - Ability to set direction and grow people while staying close enough to the work to pair on hard problems, review system design, write code at the right moments, and model strong engineering judgment. - Strong product judgment, able to reason from customer need to product experience to technical architecture. - Excitement about AI as an execution layer, understanding that real customer value comes from orchestration, tools, workflows, evaluation, approvals, observability, and recovery. - Hands-on or deeply practical familiarity with LLM applications, agentic systems, workflow orchestration, evals, and the tradeoffs involved in moving from prototype to production. - High bar for quality and trust, knowing that an assistant acting on personal finances has to be accurate enough to earn the right to act. - Comfortable driving outcomes in ambiguity, identifying the crux, sequencing the work, making tradeoffs, and keeping a team moving. - Ability to explain the why, create alignment across functions, and give engineers enough context to make good local decisions. - Tenacious learner, staying engaged with changes in AI, team workflows, product expectations, and operational systems. - Energized by continuous improvement, noticing where workflows are painful or where the team has accepted too much uncertainty as normal. - Technical depth and range across backend services, product surfaces, data systems, AI workflows, operational tooling, or consumer fintech products. - Comfortable with urgency, helping a team move quickly while keeping both hands on the wheel. Requirements - Experience building or leading teams that combine probabilistic AI systems with deterministic execution paths, operational workflows, or human-in-the-loop review. - Experience with TypeScript, Node, React, React Native, GraphQL, Postgres, LLM applications, agentic systems, workflow orchestration, or consumer fintech products. - A track record of creating team infrastructure from the ground up: hiring practices, onboarding, technical playbooks, coaching systems, review rituals, or quality frameworks. - Experience improving reliability, observability, alerting, incident response, operational quality, or other systems that make software safer and more dependable over time. - Experience partnering deeply with Product, Design, Data, Operations, Legal, Support, or other cross-functional teams in a sensitive customer domain. - A visible habit of raising the bar for both product craft and engineering rigor without making the team feel buried under process. - Firsthand experience building products where customer trust, permissions, explainability, and recovery paths are central to the experience. Benefits - Health, Dental & Vision Plans - Competitive Pay - 401k Matching - Unlimited PTO - Lunch daily (in-office only) - Snacks & Coffee (in-office only) - Commuter benefits (in-office only) Additional information: Salary range of $200,000 - $280,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.

Role Description Estamos em busca de um(a) Sr AI Engineer para fazer parte de um time dedicado exclusivamente à Inteligência Artificial, focado em acompanhar os avanços mais recentes em LLMs e IA Generativa e transformá-los rapidamente em soluções de alto impacto para Educação. Trabalhará ao lado de outros AI Engineers e especialistas pedagógicos, em um ambiente de aprendizado contínuo, experimentação e colaboração, desenvolvendo produtos que chegam a milhões de estudantes em todo o Brasil. - Liderança e Impacto no Negócio: - Ser referência técnica para engenheiros(as) mais juniores do time de AI Engineering, disseminando boas práticas e direcionando escolhas arquiteturais de Engenharia de Software e Engenharia de IA; - Identificar proativamente oportunidades de aplicação de IA Generativa e Machine Learning que gerem impacto real nos principais indicadores de negócio; - Traduzir necessidades de negócio em soluções técnicas viáveis utilizando LLMs e dados; - Co-criar soluções com time de Produto, Engenharia de Software e design. - Engenharia de IA e Software: - Liderar o desenvolvimento de soluções com LLMs de fronteira que interagem com milhões de usuários do meio de Educação; - Arquitetar e desenvolver aplicações avançadas de IA utilizando Vector Databases, LLMs multimodais, Single Agents, Multi-Agent systems; - Desenvolver e otimizar pipelines de anotação, validação e qualidade para aplicações de LLMs, implementando evals, LLM-as-a-judge, métricas de avaliação, etc.; - Evoluir e otimizar a stack de desenvolvimento do time (CI/CD, infraestrutura para LLMs, governança e otimização de custos de API/computação). - Inovação e Prototipagem: - Interagir com professores, alunos, famílias, diretores e especialistas pedagógicos para co-criar soluções para o meio educacional; - Construir e influenciar o time a construir com velocidade e adaptabilidade protótipos para validação rápida de hipóteses de negócio e técnicas; - Ser referência no time de acompanhamento de novos papers, blogs técnicos e principais conferências globais de IA para trazer tendências, novas bibliotecas e técnicas de IA para o time. Qualifications - Interesse genuíno no tema de Educação e aprendizado humano; - Sólida experiência em Ciência de Dados, Engenharia de Machine Learning, Engenharia de Software (focada em dados) ou no desenvolvimento robusto de aplicações baseadas em LLMs; - Domínio avançado de Python, Git e profundidade em boas práticas de Engenharia de Software (Clean Code, Testes Unitários, Design Patterns); - Excelente habilidade de comunicação para traduzir conceitos técnicos complexos para stakeholders de produto e negócios; - Experiência prévia com mentoria técnica de profissionais de engenharia ou dados; - Inglês avançado para leitura de literatura técnica, documentações e artigos científicos na fronteira do conhecimento de IA. Requirements - Expertise em temas pedagógicos; - Experiência profunda com LLMs em produção e alta escala; - Experiência profunda em construção de sistemas que requerem interação recorrente com experts de domínio. Benefits - Vale alimentação e/ou refeição Flash; - Plano de saúde e odontológico SulAmerica; - Vale transporte para vagas presenciais e híbridas; - Licença maternidade e paternidade estendida; - Auxílio creche; - Cuidado com a saúde: parceria com a Wellhub e Zenklub; - Incentivo à educação; - Desconto em passagens aéreas; - Parceria com plano de saúde para Pet; - Acesso aos materiais didáticos Arco para filhos de colaboradores; - Parcerias para MBA e Pós Graduação.