AI Deployment Engineer
crewAI
full-time
Posted on:
Location Type: Remote
Location: United States
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About the role
- 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.
Requirements
- 3+ years in customer-facing technical role (Forward Deployed Engineer, Implementation Engineer, Technical Account Manager, or similar).
- Strong proficiency in Python and hands-on experience with containerized deployments (Docker, Kubernetes), and Agentic AI Stack (observability, RAG, etc).
- Familiarity with AI/ML concepts and technologies, including LLMs, AI agent frameworks, RAG patterns, and prompt engineering.
- Experience troubleshooting distributed systems in production—networking, scheduling, resource management, and observability.
- Exceptional communication skills, with the ability to translate complex technical issues into clear customer communications and executive briefings.
- Knowledge of workflow orchestration, multi-agent systems, or distributed computing is a strong plus.
- Bachelor's degree in Computer Science, Engineering, or a related technical field preferred.
- Experience building GenAI solutions, working with various databases (SQL, NoSQL), or contributing to open-source AI agent projects is a significant bonus.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonAgentic AI StackDockerKubernetesAI/ML conceptsLLMsRAG patternsprompt engineeringdistributed systemsGenAI solutions
Soft Skills
exceptional communication skillscustomer-facingrelationship buildingtechnical workshopstraining sessionsproactive identificationcollaborationstructured feedbacktroubleshootingadaptability
Certifications
Bachelor's degree in Computer ScienceBachelor's degree in Engineering