Responsibilities
- Lead the design and hands-on implementation of production-level machine learning and Generative AI systems on AWS, with understanding across multi-cloud platforms.
- Serve as a technical advisor to customers, guiding them from discovery through deployment and optimization of large-scale AI/ML workloads.
- Transform complex business challenges into secure, reliable, cost-effective, and observable cloud architectures.
- Drive internal and customer-facing AI/ML maturity by converting custom implementations into reusable patterns that shape future product development.
- Prioritize customer environment health, product adoption, proactive technical engagement, and collaboration with account teams.
- Act as a go-to technical expert for customers, delivering high-impact improvements in cost, reliability, security, and performance.
- Design and assist in deploying cost-optimization strategies such as resource rightsizing, reserved instances, and storage efficiency.
- Develop and support architectures that enhance system reliability and resilience, including high availability and disaster recovery.
- Architect solutions that improve security through IAM policies, network segmentation, data protection, and least-privilege access.
- Create systems that reduce operational burden via automation, self-service tools, policy enforcement, and guardrails.
- Plan and lead structured technical engagements including optimization workshops, security reviews, and architecture assessments.
- Address advanced support inquiries requiring deep cloud engineering knowledge, delivering clear and effective resolutions.
- Apply specialized knowledge in ML and Generative AI, including training/inference pipelines, GPU utilization, scaling, and cost management, along with MLOps and integration with monitoring and FinOps.
- Convert ad-hoc field solutions into standardized, reusable assets to improve customer outcomes and internal capabilities.
- Develop 'gravel roads'—reusable patterns such as playbooks, Terraform modules, templates, and documentation—from customer implementations.
- Deliver structured input to product and engineering teams on product limitations and usability challenges observed in practice.
- Identify and recommend new automation opportunities and telemetry enhancements in DCI to improve future field engineering efficiency.
- Directly contribute to DCI through feature suggestions, code contributions, or end-to-end ownership of specific features.
- Build agents, scripts, and internal tools that scale technical expertise across the organization.
- Support team growth through documentation, demonstrations, training, and knowledge-sharing sessions for engineers and customer success staff.
- Function as an integrated technical partner within account teams.
- Collaborate with Customer Success and Account Managers to achieve measurable customer outcomes.
- Own technical execution including deployment, integration, automation adoption, proactive monitoring, and repeatable optimization frameworks.
- Work alongside customer engineers and architects to turn ambiguous issues into actionable technical plans and sustainable implementations.
- Collaborate with peer Field Delivery Engineers on complex, cross-domain projects, jointly refining designs and engagement strategies.
Work Arrangement
Remote (Worldwide) — UK, Ireland, Estonia, Sweden, Netherlands, Israel, Eastern Europe, Portugal
Full-time employee benefits include
- Unlimited Vacation
- Flexible Working Options
- Health Insurance
- Parental Leave
- Employee Stock Option Plan
- Home Office Allowance
- Professional Development Stipend
- Peer Recognition Program
The job is available to
Full-Time Employees in UK, Ireland, Estonia, Sweden, the Netherlands, and Israel.
The job is open to
contractors in Eastern Europe or Portugal.
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