• Lead the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments). • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization. • Translate complex business problems into cloud architectures that are secure, reliable, cost-efficient, and observable. • Help evolve how DoiT uses AI/ML internally and with customers by turning one-off solutions into reusable patterns and “gravel roads” that influence the product roadmap. • Focus more on install base health, product adoption, proactive engagements, and account-team work.

• Lead the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments). • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization. • Translate complex business problems into cloud architectures that are secure, reliable, cost-efficient, and observable. • Help evolve how DoiT uses AI/ML internally and with customers by turning one-off solutions into reusable patterns and “gravel roads” that influence the product roadmap. • Focus on install base health, product adoption, proactive engagements, and account-team work.

• Lead the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments). • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization. • Translate complex business problems into cloud architectures that are secure, reliable, cost-efficient, and observable. • Help evolve how DoiT uses AI/ML internally and with customers by turning one-off solutions into reusable patterns and 'gravel roads' that influence the product roadmap. • Focus more on install base health, product adoption, proactive engagements, and account-team work.

• Lead the design and implementation of production-grade ML and Generative AI solutions on AWS (with awareness of multi-cloud environments). • Act as a hands-on expert and trusted advisor for customers running AI/ML workloads at scale, from initial discovery through deployment and optimization. • Translate complex business problems into cloud architectures that are secure, reliable, cost-efficient, and observable. • Help evolve how DoiT uses AI/ML internally and with customers by turning one-off solutions into reusable patterns and “gravel roads” that influence the product roadmap. • Focus more on install base health, product adoption, proactive engagements, and account-team work. • Be the trusted cloud engineer customers lean on for high-impact technical optimization work across cost, reliability, security, and performance. • Design and help implement solutions that improve cost efficiency (rightsizing, reservations/commitments, storage optimization, etc.), increase reliability and resilience (HA/DR architectures, SLO/SLA‑aware designs), strengthen security posture (IAM, network segmentation, data protection, least‑privilege), and reduce operational toil (automation, self‑service, guardrails, policy enforcement). • Plan and deliver structured engagements such as Cloud Optimization Sessions, cost/efficiency/performance workshops, security posture or reliability reviews, and architecture deep dives / "well‑architected" style assessments. • Respond to Expert Inquiry / support requests that require deep cloud engineering expertise, ensuring high‑quality, well‑explained resolutions. • Turn one-off field work into reusable assets that improve both customer outcomes and the product itself.