Top Tech Jobs & Startup Jobs

Embed with customers to design, build, and deploy production agentic AI systems. Architect multi-agent workflows, prototype and harden LLM-based agent frameworks, implement stateful memory and evaluation/safety guardrails, optimize latency and cost, and translate field feedback into platform improvements while collaborating with product and engineering teams.

Lead design, deployment, and optimization of production-scale LLM inference systems. Embed with customers to debug latency, profile GPU usage, implement cluster-scale strategies (prefill/decode disaggregation, KV-cache routing, tiered caching, MoE parallelism), drive hardware efficiency (quantization, parallelism, batching), build internal tooling, and contribute improvements upstream to open-source inference frameworks.

Lead strategy, roadmap and full lifecycle for Cloudways products. Conduct customer discovery, define requirements, build business cases, measure product success, and drive adoption and growth. Collaborate with Engineering, UX, Data and GTM teams, use AI tools to accelerate work, manage launches, prioritize issues, and align stakeholders with limited oversight.

Serve as a strategic HR partner to managers, coaching on team dynamics and ER, driving data-informed people decisions via Workday/HRIS, executing people cycles (performance, comp, surveys), and leveraging AI and digital tools to streamline HR workflows.

As a Talent Success Business Partner, support HR processes including employee lifecycle, performance management, and engagement in a fast-paced environment.

Technical leader designing and implementing massive-scale, stateful multi-agent multi-turn simulation and evaluation systems. Build persona synthesis pipelines, what-if benchmarking frameworks, durable workflow orchestration, and high-performance APIs while integrating LLMs and agentic architectures. Drive architecture, mentor engineers, lead cross-functional strategy, and ensure scalability, reliability, and observability for AI feedback and evaluation infrastructure.

Lead and grow the Inference Orchestration engineering team to design, build, and operate Kubernetes-based AI infrastructure at scale. Drive scheduling, GPU utilization, topology-aware placement, checkpoint/restore for long jobs, fault tolerance, model distribution, security isolation, and cross-functional delivery to meet performance, cost, and reliability goals.

Serve as a strategic technical partner for key customers: design and advise on cloud architectures, run technical workshops, proactively monitor usage, resolve escalations with engineering, drive retention and expansion, and develop tools and documentation to improve Technical Account Management efficiency.

Own and operate DigitalOcean's billing control plane: triage escalated billing/support issues, build automation and revenue-assurance tooling, ensure platform reliability, collaborate across engineering, product, finance, and support, and support new product operational launches.

Provide personalized support for account, billing, and platform issues; educate customers on platform capabilities and best practices; triage and escalate incidents; create and update knowledge base content; identify recurring issues and drive product/process improvements while collaborating with the team.