Senior Cloud Architect, Delivery (GenAI) - Doit International

Experience 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions , including production workloads. Proven track record designing and operating large, distributed systems on AWS , selecting appropriate services and patterns to meet business and technical goals.

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) 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. Bring domain depth in: ML / GenAI - deploying and operating ML/GenAI workloads (training and inference), GPU utilization, scaling, and cost control; MLOPS and integrating workloads with monitoring, logging, and FinOps; safe and efficient use of managed AI services. Turn one‑off field work into reusable assets that improve both customer outcomes and the product itself. Convert one‑off customer solutions into Gravel Roads - reusable patterns such as playbooks, Terraform modules, CloudFlow templates, cloud diagrams, Composer Recipes -> DCI Insights, and internal /external documentation. Provide structured feedback to the DoiT Product and Engineering teams on: product gaps and friction points discovered in real‑world usage new opportunities for automation and workload lenses within DCI telemetry and tracking that would make future FDE work more efficient Contribute directly to DCI where appropriate - from feature requests and feedback, to contributing code, to owning specific DCI features end‑to‑end. Build agent skills, scripts, and internal tooling that codify your expertise and scale it across the team. Contribute to internal enablement: share learnings via documentation, demos, office hours, or training sessions for other FDEs and Customer Success team members. Operate as an embedded technical partner inside the account team. Work in the account team model alongside Customer Success Managers (CSMs), Account Managers (AMs) to deliver impactful outcomes. Own the technical depth lane: technical deployment & integration, automation & platform adoption, signal‑based proactive engagement, and most importantly, repeatable Cloud Optimization solutions. Partner with customers' engineers, architects, and FinOps teams to translate vague pain points into concrete technical optimization plans - and help them ship changes that stick and create continuous value. Co‑deliver complex or multi‑domain engagements with peer FDEs (for example, infra + data + ML/GenAI), reviewing and refining designs, and engagement plans together. Communicate complex technical topics clearly to both engineers and non‑technical stakeholders (FinOps, finance, leadership), and maintain clear documentation of architectures, decisions, and implemented changes so customers and fellow FDEs can sustain and build on your work. Contribute to a culture of continuous improvement within the global FDE community through design reviews, internal forums, enablement sessions, and experimentation. Become an expert in DCI and use it hands‑on to drive concrete customer outcomes. Master DoiT Cloud Intelligence™ products and services - including Cloud Analytics, DCI Insights, Cloud Composer, CloudFlow, DataHub, PerfectScale, and other Enterprise Platforms. Use DCI hands‑on to: Build and operationalize Cloud Analytics and Allocations to create dashboards and reports for customer engineering, finance, and leadership. Use DCI Insights to identify and prioritize cost, risk, and reliability opportunities, and shepherd them through to closure. Implement Cloud Composer queries, build recipes that result in hand-crafted insights across all customers' engineering use cases. Build CloudFlow automations (e.g., anomaly routing, scheduled actions, guardrails, policy enforcement). Use Built in Integrations such and utilize DataHub and other workload‑intelligence features to optimize key business and workload data inside DCI. Help customers embed DCI into existing observability, CI/CD, and governance processes so it becomes trusted and indispensable in day‑to‑day cloud operations.

Experience 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions , including production workloads. Proven track record designing and operating large, distributed systems on AWS , selecting appropriate services and patterns to meet business and technical goals.