Are you ready to lead a global SRE team while shaping cloud‑native architectures that can be rebuilt from the ground up—fully automated, secure, and scalable by design? About the Business: LexisNexis® Risk Solutions provides customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we ultimately help make communities safer, insurance rates more accurate, commerce more transparent, business decisions easier and processes more efficient. You can learn more about LexisNexis Risk at the link below, risk.lexisnexis.com About the Team: You will be joining the Core SRE Team in Business Services, a team that oversees all the applications and infrastructure in the biggest business unit in LexisNexis Risk Solutions. We build cloud environments, migrate on prem applications to the cloud, work with self-hosted and 3rd party solutions. The successful candidate is a self-starter who assesses the situation, collaboratively develops a solution, and takes the initiative to improve performance, cost, and reliability at each opportunity. About the Role: This role will lead a team of SRE’s across the USA and India regions. You will be the point of contact for the Core SRE team and other product specific DevOps and SRE teams in terms of addressing blockers, helping with best practices for cloud architecture, paving the ways in terms of new landscapes and SaaS solutions. Big part of the role requires security focus as we have many different solutions. You will set the example for a collaborative and forward-thinking team working with a diverse range of technologies so that they are able to enjoy an amiable and supportive environment, benefit from our investment in team skills-building and cross-training, and where we leverage each other’s strengths. Responsibilities: - Deliver cloud-native solutions and patterns that are highly elastic. - Empower stakeholders and reduce toil through self-service pipelines. - Mentor your team in solving deep technical issues, advanced cloud infrastructure topics, and complex coding problems. - Set an example of methodical, systematic task execution for your team. - Work with project managers and stakeholders to provide status and reporting. - Act as an ambassador to other teams, finding common ground and defining clear agreements. - Drive projects to schedule. - Perform code reviews with an eye toward rigor and best practice. - Apply continuous process improving techniques across the operation. - Automate everything. - You will ensure that everything is IAC, and that your team’s infra can be rebuilt from the ground up without relying on manual configurations or the Azure/AWS Portal. Key technologies: Azure, GitHub, Azure Kubernetes, Argo / Helm, Terraform, Docker, JFrog, Grafana, Networking, Information Security, Redis Requirements: - Leadership/design of application and/or infrastructure migration projects from on-prem to cloud - Proven expert in partnering and leading technology resources in solving complex business needs - Cloud architecture design and implementation to solve key business needs and meet team goals - Experience with Terraform and GitHub Actions Working for You: We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: - Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs. - Life Assurance Policies: Providing financial security for your loved ones. - Modern Family Benefits: Support for maternity, paternity, and adoption needs. - Long Service Award: Recognition for your dedication and loyalty. - Celebratory Allowance/Gifts: Marking special occasions to celebrate with you. - Flexible Benefits Plan : Offering you wider choice of services and products - Employee Assistance Program : Access support for personal and work-related challenges. - Flexible Working Arrangements: Balance work and personal life effectively. - Access to Learning and Development Resources: Empowering your professional growth. U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates. Base Pay Range for CO is $118,300 - $219,800. Base Pay Range for IL is $124,200 - $230,800. Base Pay Range for Chicago, IL is $130,200 - $241,800. Base Pay Range for MD is $124,200 - $230,800. Base Pay Range for NY is $130,200 - $241,800. Base Pay Range for New York City is $142,000 - $263,800. Base Pay Range for Rochester, NY is $118,300 - $219,800. Base Pay Range for OH is $112,400 - $208,800. Base Pay Range for NJ is $143,220- $228,780. This job is eligible for an annual incentive bonus. Application deadline is 05/09/2026. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here. Please read our Candidate Privacy Policy. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights.

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.

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.