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.

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.

• Deliver rapid, high-quality output, leveraging AI tooling to accelerate development and improve code quality. • Provide feedback and participate in code reviews to ensure implementation meets requirements. • Participate in architectural discussions and influence the team’s and POS teams’ technical roadmap. • Mentor and provide technical guidance to other team members. • Partner closely with the developer community, release manager and QA functions to develop DevEx, feature flag (FF) management and release strategies. • Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.

• Manage and troubleshoot complex distributed large-scale software systems • Build scalable, secure and reliable container-based infrastructure • Automate software delivery processes with CI/CD pipelines • Collaborate within DevOps, development, security, compliance teams • Ensure the security and stability of the infrastructure • Active participation in building new infra pieces like ClickHouse, SaaS • Improvement and strengthening DRP • On-going DevOps activities in support of development/deployment/testing processes