• Deliver high-impact AI engagements • Lead hands-on delivery for GenAI implementation engagements, funded implementation projects, technical proof-of-value engagements, and other customer-facing AI initiatives. • Translate customer goals into practical architectures, implementation plans, and measurable technical outcomes. • Build, configure, and validate AWS-native AI and data solutions, with emphasis on production-ready architectures and services. • Own technical execution from discovery through delivery, including design reviews, workshops, implementation support, and executive-ready readouts. • Step into complex customer situations where technical depth, speed, and credibility are required. • Drive outcomes across the four FE growth pillars • Support product adoption by helping customers implement and integrate DoiT products as part of AI engagements and broader cloud initiatives. • Contribute to new logo acquisition by using technical consulting, implementation engagements, and proof-of-value work to help open and progress new opportunities. • Expand the install base by helping existing customers adopt advanced features, launch new workloads, and move to higher-value product and service motions. • Strengthen partner leadership by collaborating with AWS partner teams, supporting funded programs, and helping DoiT show up as a strategic technical partner in AI-related motions. • Turn field work into repeatable plays • Identify patterns, reusable assets, and “gravel road” solutions that should become standard delivery approaches, playbooks, or product feedback. • Help move successful one-off customer work into repeatable solution packages, templates, and standardized offerings for the broader team. • Contribute to standardization of engagement sizing, delivery approach, and technical assets to improve team efficiency over time. • Work cross-functionally to close and deliver • Partner closely with Solution Engineers, Account Managers, Customer Success Managers, Engagement Managers, and partner teams to scope and execute the right work at the right time. • Provide technical leadership during discovery, planning, handoff, and delivery. • Help ensure customer engagements are well-scoped, well-documented, and tied to clear success criteria. • Operate with discipline • Maintain clear visibility into active work, risks, dependencies, and next steps. • Use the team’s operating systems and workflows to keep customer engagement data current and measurable. • Contribute to adoption playbooks, funding workflows, Jira hygiene, and the management cadence needed to scale the Field Engineering model.

• Deliver high-impact AI engagements • Lead hands-on delivery for GenAI implementation engagements, funded implementation projects, technical proof-of-value engagements, and other customer-facing AI initiatives. • Translate customer goals into practical architectures, implementation plans, and measurable technical outcomes. • Build, configure, and validate AWS-native AI and data solutions, with emphasis on production-ready architectures and services. • Own technical execution from discovery through delivery, including design reviews, workshops, implementation support, and executive-ready readouts. • Step into complex customer situations where technical depth, speed, and credibility are required. • Drive outcomes across the four FE growth pillars • Support product adoption by helping customers implement and integrate DoiT products as part of AI engagements and broader cloud initiatives. • Contribute to new logo acquisition by using technical consulting, implementation engagements, and proof-of-value work to help open and progress new opportunities. • Expand the install base by helping existing customers adopt advanced features, launch new workloads, and move to higher-value product and service motions. • Strengthen partner leadership by collaborating with AWS partner teams, supporting funded programs, and helping DoiT show up as a strategic technical partner in AI-related motions. • Turn field work into repeatable plays • Identify patterns, reusable assets, and “gravel road” solutions that should become standard delivery approaches, playbooks, or product feedback. • Help move successful one-off customer work into repeatable solution packages, templates, and standardized offerings for the broader team. • Contribute to standardization of engagement sizing, delivery approach, and technical assets to improve team efficiency over time. • Work cross-functionally to close and deliver • Partner closely with Solution Engineers, Account Managers, Customer Success Managers, Engagement Managers, and partner teams to scope and execute the right work at the right time. • Provide technical leadership during discovery, planning, handoff, and delivery. • Help ensure customer engagements are well-scoped, well-documented, and tied to clear success criteria. • Operate with discipline • Maintain clear visibility into active work, risks, dependencies, and next steps. • Use the team’s operating systems and workflows to keep customer engagement data current and measurable. • Contribute to adoption playbooks, funding workflows, Jira hygiene, and the management cadence needed to scale the Field Engineering model.

• Deliver high-impact AI engagements • Drive outcomes across the four FE growth pillars • Turn field work into repeatable plays • Work cross-functionally to close and deliver • Operate with discipline

• Deliver high-impact AI engagements • Lead hands-on delivery for GenAI implementation engagements, funded implementation projects, technical proof-of-value engagements, and other customer-facing AI initiatives. • Translate customer goals into practical architectures, implementation plans, and measurable technical outcomes. • Build, configure, and validate AWS-native AI and data solutions, with emphasis on production-ready architectures and services. • Own technical execution from discovery through delivery, including design reviews, workshops, implementation support, and executive-ready readouts. • Step into complex customer situations where technical depth, speed, and credibility are required. • Drive outcomes across the four FE growth pillars • Support product adoption by helping customers implement and integrate DoiT products as part of AI engagements and broader cloud initiatives. • Contribute to new logo acquisition by using technical consulting, implementation engagements, and proof-of-value work to help open and progress new opportunities. • Expand the install base by helping existing customers adopt advanced features, launch new workloads, and move to higher-value product and service motions. • Strengthen partner leadership by collaborating with AWS partner teams, supporting funded programs, and helping DoiT show up as a strategic technical partner in AI-related motions. • Turn field work into repeatable plays • Identify patterns, reusable assets, and “gravel road” solutions that should become standard delivery approaches, playbooks, or product feedback. • Help move successful one-off customer work into repeatable solution packages, templates, and standardized offerings for the broader team. • Contribute to standardization of engagement sizing, delivery approach, and technical assets to improve team efficiency over time. • Work cross-functionally to close and deliver • Partner closely with Solution Engineers, Account Managers, Customer Success Managers, Engagement Managers, and partner teams to scope and execute the right work at the right time. • Provide technical leadership during discovery, planning, handoff, and delivery. • Help ensure customer engagements are well-scoped, well-documented, and tied to clear success criteria. • Operate with discipline • Maintain clear visibility into active work, risks, dependencies, and next steps. • Use the team’s operating systems and workflows to keep customer engagement data current and measurable. • Contribute to adoption playbooks, funding workflows, Jira hygiene, and the management cadence needed to scale the Field Engineering model.