CrewAI

• Own the full customer lifecycle for a portfolio of LATAM enterprise accounts, from onboarding through renewal and expansion • Build and maintain deep relationships with customer stakeholders and executive sponsors, acting as a trusted strategic advisor throughout their AI journey • Define and track success metrics, health scores, and adoption milestones for each account; translate platform usage into business outcomes and ROI • Design and execute activation strategies — champion programs, office hours, usage reviews, and customized workshops — that drive meaningful platform adoption • Lead business reviews (QBRs) with customer leadership to demonstrate realized value and align on next steps • Proactively identify expansion opportunities and partner with sales on upsell and cross-sell initiatives • Orchestrate cross-functional teams (Product, Engineering, Solutions) to resolve escalations and remove blockers for customer success • Serve as the voice of the LATAM customer internally, surfacing feedback, regional nuance, and product gaps to Product and Engineering • Develop and scale enablement resources — playbooks, onboarding guides, training materials — tailored to LATAM markets • Build and nurture champion communities and power user networks within customer organizations

Role Description As a Customer Success Manager, LATAM at CrewAI, you will be the strategic partner for our growing portfolio of enterprise customers across Brazil and Latin America. You will own the customer relationship from onboarding through renewal and expansion — becoming a trusted advisor who helps organizations translate their AI investments into measurable business outcomes. This is a high-impact, relationship-driven role at the frontier of enterprise AI, and a pivotal hire as we plant our flag in the region. - Own the full customer lifecycle for a portfolio of LATAM enterprise accounts, from onboarding through renewal and expansion. - Build and maintain deep relationships with customer stakeholders and executive sponsors, acting as a trusted strategic advisor throughout their AI journey. - Define and track success metrics, health scores, and adoption milestones for each account; translate platform usage into business outcomes and ROI. - Design and execute activation strategies — champion programs, office hours, usage reviews, and customized workshops — that drive meaningful platform adoption. - Lead business reviews (QBRs) with customer leadership to demonstrate realized value and align on next steps. - Proactively identify expansion opportunities and partner with sales on upsell and cross-sell initiatives. - Orchestrate cross-functional teams (Product, Engineering, Solutions) to resolve escalations and remove blockers for customer success. - Serve as the voice of the LATAM customer internally, surfacing feedback, regional nuance, and product gaps to Product and Engineering. - Develop and scale enablement resources — playbooks, onboarding guides, training materials — tailored to LATAM markets. - Build and nurture champion communities and power user networks within customer organizations. Qualifications - 4 - 7+ years of customer-facing experience in Customer Success, Account Management, or Strategic Partnerships at a SaaS or enterprise software company. - Fluent in Portuguese and English; Spanish proficiency strongly preferred. - Proven track record of owning customer outcomes end-to-end — activation, adoption, retention, and expansion. - Experience managing a portfolio of enterprise accounts and navigating complex, multi-stakeholder environments. - Demonstrated ability to connect platform usage to business outcomes and articulate ROI to both business and executive audiences. - Strong facilitation skills — able to design and lead workshops, training sessions, and business reviews that move customers to action. - Exceptional communication and executive presence; can present with confidence at the C-suite level and translate complex concepts for diverse audiences. - Enough technical fluency to be credible with engineering stakeholders and collaborate effectively with technical teams. Preferred Qualifications - Prior experience with AI, ML, or automation platforms in a customer-facing role. - Familiarity with agentic AI concepts, large language models (LLMs), or multi-agent frameworks. - Experience building champion networks, power user communities, or internal advocacy programs within enterprise accounts. - Deep knowledge of LATAM enterprise buying culture, regional regulatory environments, and market nuance. - Background in a high-growth startup or early-stage product company; comfortable operating with ambiguity and evolving processes. - Experience working cross-functionally with Product and Engineering to close customer feedback loops. - Proficiency with CRM and CS tooling. Who You Are - Customer Obsessed: You treat every customer’s success as your own — you anticipate problems before they happen and take ownership of outcomes, not just activities. - Builder Mindset: You don’t wait for customers to engage — you build the programs, communities, and frameworks that make engagement inevitable. - Clear Communicator: You can walk a VP of Engineering through an architecture decision and a CMO through an ROI analysis — in Portuguese, Spanish, or English. - AI-Curious: You follow the AI ecosystem closely, bring genuine curiosity to every customer conversation, and help customers see what’s possible with agentic AI. - Collaborative: You thrive in cross-functional environments, share your playbook generously, and raise the bar for everyone around you. Benefits - Competitive salary and equity in a fast-growing AI infrastructure company. - Opportunity to work at the frontier of agentic AI with some of the most ambitious enterprise teams in the world. - Remote-friendly culture with flexible working arrangements. - Dedicated budget for learning, conferences, and professional development. - Access to cutting-edge LLM credits, tooling, and infrastructure. - Collaborative, low-ego team that moves fast and celebrates wins together.

• Be the senior technical point of contact for enterprise customers, owning the hardest issues end-to-end and responding with clarity and speed. • Deeply use and know the product: Crews, Flows, the Control Plane well enough to resolve the majority of issues without escalating, and to spot bugs customers haven't even reported. • Reproduce, diagnose, and triage technical issues: read logs and traces, isolate root cause, and resolve directly where possible. • Own clean handoffs to engineering: when something must escalate, file a well-defined ticket with reproduction steps, context, and severity. Keep the handoff between the support and engineering systems coherent so engineers aren't re-reading threads to figure out what's being asked. • Define and own support SLAs, severity levels, and escalation paths so the loudest customer doesn't automatically become the highest priority — and continuously improve them. • Build and maintain the knowledge base, FAQs, and troubleshooting docs, and improve product docs where they make false assumptions about customer setup. • Set up structured customer onboarding so new enterprise users get to value quickly. • Close the loop: synthesize recurring issues and feedback into clear signal for product and engineering, and help set the direction support takes as it grows.

Role Description You're the senior technical anchor for enterprise support: the person who sets the standard for how we diagnose, resolve, and learn from customer issues, and who builds the process the function runs on. You'll work the hardest problems directly and define how support operates: triage, severity, escalation, and the feedback loop into product and engineering. You are not a proxy that forwards messages, but someone who deeply understands the product and resolves issues end-to-end. Our focus right now is enterprise support. You'll be the senior technical line for our enterprise customers, reproducing and diagnosing problems, resolving what you can, and handing off what you can't with the full context engineering needs. As the most experienced person in the seat, you'll own the SLAs, severity model, and escalation paths the team operates on, and raise the technical quality of support across the board. This role exists to make enterprise support excellent and to build the foundation it scales on. We're looking for someone who will set the technical bar, protect engineering's focus by filtering and enriching what reaches them, and build a customer experience that feels structured, fast, and trustworthy. What You'll Do - Be the senior technical point of contact for enterprise customers, owning the hardest issues end-to-end and responding with clarity and speed. - Deeply use and know the product: Crews, Flows, the Control Plane well enough to resolve the majority of issues without escalating, and to spot bugs customers haven't even reported. - Reproduce, diagnose, and triage technical issues: read logs and traces, isolate root cause, and resolve directly where possible. - Own clean handoffs to engineering: when something must escalate, file a well-defined ticket with reproduction steps, context, and severity. Keep the handoff between the support and engineering systems coherent so engineers aren't re-reading threads to figure out what's being asked. - Define and own support SLAs, severity levels, and escalation paths so the loudest customer doesn't automatically become the highest priority — and continuously improve them. - Build and maintain the knowledge base, FAQs, and troubleshooting docs, and improve product docs where they make false assumptions about customer setup. - Set up structured customer onboarding so new enterprise users get to value quickly. - Close the loop: synthesize recurring issues and feedback into clear signal for product and engineering, and help set the direction support takes as it grows. Qualifications - 5+ years in technical support, developer support, solutions, or a similar customer-facing technical role, including time as a senior or anchor on the team. - Genuinely technical: comfortable reading logs, stack traces, and API responses; able to navigate Python and the command line; can reason about how a distributed system fails. - Familiarity with LLMs, agents, or developer tools, or the ability to ramp quickly and use the product daily. - Strong written communication: you can explain a fix clearly and write a ticket an engineer can act on immediately. - Process ownership: you've defined triage rules, SLAs, severity models, or escalation paths before, not just followed them, and you can show how it raised the quality of support. - Empathetic, patient, and energized by helping people succeed; comfortable working independently and setting your own direction in a fast-paced remote startup. Requirements - Bonus: experience with support/issue tooling (ticketing systems, Linear, or similar); prior experience supporting an open-source developer community; experience standing up or overhauling a support function.

Title: Senior Fullstack Engineer (Ruby / Python / React) Location: San Francisco CA US Full time Hybrid Must be based in SF bay area We are looking for an experienced Fullstack Engineer to join our dynamic team at crewAI. You will be instrumental in advancing our crewAI+ platform, a Ruby on Rails application that heavily leverages Python services. As a key member of our engineering team, you will contribute to both backend and frontend development, ensuring seamless integration and robust performance. This role is ideal for a self-motivated individual with a strong background in Ruby, Python, and React, who excels in a collaborative and innovative environment. Requirements - At least 7 years of programming experience, with a significant portion dedicated to fullstack Ruby development. - Extensive experience with Ruby, specifically in fullstack development. - Strong knowledge and practical experience with Python services. - Proficiency in React for frontend development. - Preferred experience with the Ruby on Rails framework. - Fluent in English with excellent verbal and written communication skills. - Strong ability to self-manage time and priorities without constant supervision. - Demonstrated problem-solving skills and innovative thinking. - Ability to work collaboratively within a team and contribute to a community-focused environment. - Flexibility to work across different programming languages and technologies as required by ongoing projects.   Responsibilities - Develop, maintain, and enhance the crewAI+ platform using Ruby on Rails and Python services. - Implement and optimize frontend components using React to create dynamic and responsive user interfaces. - Collaborate with cross-functional teams to design and deliver high-quality solutions. - Manage and prioritize tasks effectively, ensuring timely delivery of projects. - Participate in technical discussions, contributing to decision-making processes and best practices. - Engage with the developer community, particularly through platforms like Discord, to foster collaboration and knowledge sharing. - Stay updated with industry trends and emerging technologies to continuously improve our platform. Benefits - Remote work flexibility. - Unlimited time off to promote work-life balance. - Competitive salary and equity package. - Opportunities for professional development and growth. - Inclusive and dynamic work culture.

• Lead technical discovery calls to deeply understand prospects' business objectives, data landscapes, and existing technology stacks. • Translate prospect requirements into solution architectures that showcase CrewAI's multi-agent capabilities, including agent role design, workflow orchestration, and integration points. • Develop and present tailored technical proposals, architecture diagrams, and scoping documents that align CrewAI's platform to prospect needs. • Build and deliver compelling product demonstrations and proof-of-concept implementations that bring CrewAI's value to life for technical and executive audiences. • Scope, manage, and execute time-boxed POC engagements, defining clear success criteria and working hands-on with prospect engineering teams. • Develop reusable demo environments, scripts, and reference architectures that accelerate the pre-sales cycle. • Partner closely with Account Executives throughout the sales cycle—from initial qualification to technical close. • Respond to RFPs, RFIs, and security questionnaires with accurate, compelling technical content. • Serve as the trusted technical advisor for prospects, handling objections and competitive differentiation conversations with confidence. • Provide feedback to Product and Engineering teams based on patterns observed across prospect engagements. • Conduct technical workshops, webinars, and conference presentations that position CrewAI as an industry leader in AI agent orchestration. • Create and maintain technical collateral—white papers, integration guides, comparison matrices—that support the sales motion. • Stay current on competitive offerings, AI/ML trends, and emerging multi-agent design patterns.

• Lead the technical integration of CrewAI's products into customers’ systems, including API integrations, data pipelines, and custom workflows. • Develop and maintain robust, scalable solutions tailored to client requirements, leveraging your expertise in Python and other relevant technologies. • Troubleshoot complex technical issues during implementation and provide timely resolutions, collaborating with our internal engineering teams as needed. • Act as the primary technical point of contact, thoroughly understanding the customers’ business objectives and technical landscapes. • Translate client needs into technical specifications and solution designs, ensuring alignment with CrewAI's product capabilities. • Design and architect CrewAI-powered agent teams, assigning specialized roles and workflows tailored to client needs. • Conduct technical workshops and training sessions for customer teams to facilitate product understanding and adoption. • Collaborate with Customer Success Engineers and Support Engineers, to ensure customers’ success and smooth operations • Deploy, configure, and optimize CrewAI-based multi-agent systems in production environments. • Develop and integrate custom agents, tools, and processes using Python and CrewAI’s open-source libraries. • Monitor deployed solutions for performance, reliability, and business value, rapidly iterating on agent roles and workflows to adapt to evolving client needs.

• Lead the technical integration of CrewAI's platform into customers' systems, including API integrations, data pipelines, authentication flows, and custom workflows. • Develop and maintain robust, scalable solutions tailored to each customer's infrastructure requirements, leveraging deep expertise in Python, Agentic AI Stack, and cloud platforms. • Troubleshoot complex technical issues during and after implementation—from container orchestration and networking problems to LLM configuration and tool integrations—providing timely resolutions and root cause analyses. • Develop and integrate custom agents, tools, and processes using Python and CrewAI's open-source and enterprise libraries. • Monitor deployed solutions for performance, reliability, and business value, rapidly iterating on agent roles and workflows to adapt to evolving customer needs. • Act as the primary technical point of contact for a portfolio of enterprise customers post-sale, building deep, trusted relationships with their engineering and leadership teams. • Conduct structured onboarding programs, technical workshops, and training sessions to drive product adoption and self-sufficiency. • Proactively identify expansion opportunities by understanding customers' evolving business objectives and mapping them to additional CrewAI capabilities. • Collaborate with Customer Success Managers and Support Engineers to ensure smooth operations and high retention. • Create and maintain deployment runbooks, best practices guides, architecture documentation, and customer-specific technical references. • Provide structured, actionable feedback to Product and Engineering based on real-world deployment patterns, pain points, and feature requests. • Contribute to internal tooling, automation, and processes that improve deployment efficiency and customer experience at scale.

• Lead the technical integration of CrewAI's products into customers’ systems, including API integrations, data pipelines, and custom workflows. • Develop and maintain robust, scalable solutions tailored to client requirements, leveraging your expertise in Python and other relevant technologies. • Troubleshoot complex technical issues during implementation and provide timely resolutions, collaborating with our internal engineering teams as needed. • Act as the primary technical point of contact, thoroughly understanding the customers’ business objectives and technical landscapes. • Translate client needs into technical specifications and solution designs, ensuring alignment with CrewAI's product capabilities. • Design and architect CrewAI-powered agent teams, assigning specialized roles and workflows tailored to client needs. • Conduct technical workshops and training sessions for customer teams to facilitate product understanding and adoption. • Collaborate with Customer Success Engineers and Support Engineers, to ensure customers’ success and smooth operations • Deploy, configure, and optimize CrewAI-based multi-agent systems in production environments. • Develop and integrate custom agents, tools, and processes using Python and CrewAI’s open-source libraries. • Monitor deployed solutions for performance, reliability, and business value, rapidly iterating on agent roles and workflows to adapt to evolving client needs.

Post-Sales · Customer-Facing · Technical Overview The AI Deployment Engineer at CrewAI is a post-sales technical role responsible for turning signed deals into production success stories. You will own the end-to-end technical relationship with enterprise customers—from initial onboarding and integration through production deployment, optimization, and ongoing expansion. This role is ideal for someone who finds deep satisfaction in solving hard infrastructure and integration problems, building lasting partnerships with customer engineering teams, and ensuring that multi-agent AI systems deliver measurable business value at scale. Key Responsibilities Technical Implementation & Integration - Lead the technical integration of CrewAI's platform into customers' systems, including API integrations, data pipelines, authentication flows, and custom workflows. - Develop and maintain robust, scalable solutions tailored to each customer's infrastructure requirements, leveraging deep expertise in Python, Agentic AI Stack, and cloud platforms. - Troubleshoot complex technical issues during and after implementation—from container orchestration and networking problems to LLM configuration and tool integrations—providing timely resolutions and root cause analyses. Deployment & Production Operations - Develop and integrate custom agents, tools, and processes using Python and CrewAI's open-source and enterprise libraries. - Monitor deployed solutions for performance, reliability, and business value, rapidly iterating on agent roles and workflows to adapt to evolving customer needs. Customer Success & Relationship Management - Act as the primary technical point of contact for a portfolio of enterprise customers post-sale, building deep, trusted relationships with their engineering and leadership teams. - Conduct structured onboarding programs, technical workshops, and training sessions to drive product adoption and self-sufficiency. - Proactively identify expansion opportunities by understanding customers' evolving business objectives and mapping them to additional CrewAI capabilities. - Collaborate with Customer Success Managers and Support Engineers to ensure smooth operations and high retention. Documentation & Feedback Loop - Create and maintain deployment runbooks, best practices guides, architecture documentation, and customer-specific technical references. - Provide structured, actionable feedback to Product and Engineering based on real-world deployment patterns, pain points, and feature requests. - Contribute to internal tooling, automation, and processes that improve deployment efficiency and customer experience at scale.