Senior Cloud Support Engineer - AI/ML & Databases at DigitalOcean Droplet Limited

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

01 Jun, 26

Salary

0.0

Posted On

03 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Kubernetes, GPU, GradientAI, AI/ML Infrastructure, Technical Leadership, Solutions Architecture, Troubleshooting, Customer Advocacy, Linux System Administration, Networking, Python, Terraform, PyTorch, TensorFlow, MLOps, Bare Metal Infrastructure

Industry

Software Development

Description

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. We are seeking an exceptional Senior Cloud Support Engineer to join our AI/ML Support team at DigitalOcean. This is our highest individual contributor level within the Support organization, representing the pinnacle of technical expertise, customer advocacy, and strategic impact. As a Senior Cloud Support Engineer, you will serve as the ultimate technical authority for our most complex customer challenges, particularly around Kubernetes (K8S) and GPU/GradientAI workloads. You'll bridge the gap between deep support expertise and solutions architecture, designing sophisticated cloud infrastructure solutions while maintaining the customer-first mentality that defines our Support organization. This role combines the architectural thinking of a Solutions Architect with the hands-on troubleshooting excellence and customer empathy expected from our Support team. You will also participate in an operational on-call rotation to support critical incidents and escalations. What You'll Do Technical Leadership & Expertise Serve as the ultimate escalation point for the most complex, business-critical customer issues across Kubernetes, GPU/GradientAI, and AI/ML infrastructure, coordinating cross-functional responses that span Engineering, Product, and Operations Architect enterprise-grade solutions for customers building large-scale AI/ML workloads on DigitalOcean, including multi-cluster Kubernetes deployments, distributed GPU training infrastructure, and hybrid/multi-cloud architectures Lead technical discovery and solution design for strategic accounts, conducting deep-dive architectural reviews, performance optimization workshops, and proof-of-concept implementations Drive resolution of systemic technical challenges by identifying patterns across customer issues, partnering with Engineering to implement platform-level improvements, and advocating for product enhancements that eliminate entire classes of problems Research and evaluate emerging technologies in the AI/ML and cloud infrastructure space, identifying opportunities for DigitalOcean to differentiate and expand our capabilities Customer Impact & Strategic Partnerships Act as a trusted technical advisor to our highest-value customers and strategic partners, building deep relationships with their technical teams and understanding their business objectives Design and deliver Professional Services engagements for enterprise customers requiring sophisticated AI/ML infrastructure implementations, managing complex project timelines, stakeholder expectations, and technical deliverables Conduct executive technical briefings and workshops that articulate DigitalOcean's platform capabilities, architectural best practices, and roadmap vision to C-level and VP-level stakeholders Partner strategically with Customer Success to drive expansion opportunities, prevent churn through proactive technical guidance, and transform technical challenges into growth opportunities Influence product strategy by synthesizing customer insights, competitive intelligence, and technical trends into actionable recommendations for Product and Engineering leadership Organizational Leadership Mentor and develop IC1-IC3 engineers through structured coaching, technical reviews, pair troubleshooting sessions, and career development guidance Design and implement support frameworks including escalation workflows, troubleshooting methodologies, automation tools, and operational best practices that elevate team capabilities Create authoritative technical documentation including architectural reference guides, troubleshooting runbooks, customer-facing solution guides, and internal training curricula Lead critical incident response for platform-wide or high-impact customer issues, coordinating cross-functional war rooms and ensuring timely, effective resolution Represent the Support organization in cross-functional initiatives, product design reviews, and strategic planning sessions, ensuring the voice of the customer influences critical decisions Domain Specialization Primary Focus Areas: Kubernetes (K8S): Expert-level architecture, troubleshooting, and optimization for production workloads GPU/GradientAI: Deep expertise in GPU infrastructure, distributed training, inference optimization, and Generative AI for our GradientAI platform Valuable Additional Expertise: Bare Metal Infrastructure: Hardware provisioning, server configuration, performance tuning Advanced Networking: BGP, VPNs, load balancing, network security, and complex multi-region architectures What You'll Add to DigitalOcean Required Experience & Expertise Technical Background 7+ years of progressive experience in technical support, solutions engineering, DevOps, or site reliability engineering roles with consistent demonstration of technical leadership 5+ years in senior technical customer-facing roles with proven ability to manage enterprise customer relationships and complex technical engagements Expert-level Kubernetes knowledge: Production-scale architecture design, cluster operations, advanced troubleshooting, performance optimization, security hardening, and networking (CNI, service meshes, ingress controllers) Deep GPU/AI/ML infrastructure expertise: Multi-GPU and multi-node training, distributed computing frameworks, GPU resource management, inference optimization, and production ML deployment patterns AI/ML Technical Depth Advanced understanding of production AI/ML pipelines including model training, optimization, deployment, and monitoring at scale Extensive experience with major ML frameworks (PyTorch, TensorFlow, Hugging Face) including distributed training strategies and production deployment patterns Expertise in GPU optimization techniques: CUDA programming concepts, TensorRT, vLLM, model quantization (INT4, INT8, FP8), and inference performance tuning Deep knowledge of MLOps practices: CI/CD for ML, model versioning, experiment tracking, feature stores, and production monitoring Experience with large-scale distributed AI/ML workloads including data parallelism, model parallelism, and mixed-precision training Cloud Infrastructure & Architecture Proven experience designing fault-tolerant, scalable cloud architectures with deep consideration for cost optimization, security, compliance, and operational excellence Expert-level Linux system administration: Kernel tuning, performance profiling, security hardening, advanced troubleshooting, and automation Advanced networking expertise: Deep understanding of TCP/IP, routing protocols, load balancing, CDNs, VPNs, network security, and troubleshooting complex network issues Strong programming skills in Python with experience in at least one additional systems language (Go, Rust, C++, or similar) Extensive experience with infrastructure-as-code (Terraform, CloudFormation, Pulumi) and configuration management tools Professional Skills Exceptional communication abilities: Can translate highly complex technical concepts into clear, actionable guidance for audiences ranging from junior engineers to C-level executives Demonstrated leadership capabilities including mentoring team members, leading cross-functional initiatives, and influencing without direct authority Strong consultative approach: Ability to discover underlying customer needs, challenge assumptions respectfully, and craft solutions that balance technical excellence with business pragmatism Track record of driving organizational improvement through process design, automation, documentation, and strategic initiatives Bare Metal & Networking (Highly Valued) Bare Metal infrastructure expertise: Server provisioning, hardware troubleshooting, BIOS/firmware management, RAID configuration, and performance tuning Advanced networking knowledge: BGP, VLANs, network automation, traffic engineering, and datacenter networking concepts Preferred Qualifications Technical Certifications & Credentials Kubernetes certifications: CKA (Certified Kubernetes Administrator), CKAD, or CKS (Certified Kubernetes Security Specialist) Advanced cloud certifications: AWS Solutions Architect Professional, GCP Professional Cloud Architect, Azure Solutions Architect Expert GPU/AI certifications: NVIDIA DLI certifications, CUDA programming certifications, or similar specialized credentials Community & Thought Leadership Open-source contributions to AI/ML projects, Kubernetes ecosystem, or infrastructure tools Published technical content: Blog posts, whitepapers, solution guides, or technical documentation demonstrating thought leadership Speaking experience at technical conferences, meetups, or webinars on topics related to cloud infrastructure, AI/ML, or DevOps Active participation in technical communities (CNCF, Kubernetes SIGs, AI/ML forums, cloud-native communities) Specialized Experience Experience with observability platforms: Prometheus, Grafana, Datadog, New Relic, or similar monitoring/alerting systems Multi-cloud or hybrid-cloud architecture experience: Designing solutions that span AWS, GCP, Azure, and on-premises infrastructure Experience with DigitalOcean or Paperspace products as a user or customer Database expertise: Experience with both relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis) databases at scale Security & compliance knowledge: Experience with SOC2, HIPAA, GDPR, or other compliance frameworks in cloud environments Key Success Metrics Technical Impact Reduction in escalation resolution time for critical customer issues through improved processes, documentation, and cross-team collaboration Customer satisfaction scores (CSAT/NPS) for your direct engagements, particularly with strategic accounts Platform stability improvements driven by your identification of systemic issues and advocacy for product enhancements Strategic Influence Product roadmap impact: Measurable influence on product decisions through customer feedback synthesis and technical requirements advocacy Expansion & retention metrics: Technical contribution to account growth, renewal success, and churn prevention for strategic customers Professional Services revenue: Successful delivery of PS engagements that drive customer success and recurring revenue Organizational Development Team capability growth: Measurable improvement in team technical skills, response times, and customer satisfaction through your mentorship and process improvements Knowledge base impact: Usage and effectiveness of documentation, runbooks, and training materials you create Cross-functional collaboration: Effectiveness in partnering with Engineering, Product, Sales, and Customer Success teams *This job is located in Hyderabad/ Bengaluru, India JR: 2026-7534 #LI-Hybrid Why You’ll Like Working for DigitalOcean We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions. We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development. We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences. We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program. DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.

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Responsibilities

This role serves as the ultimate technical authority for complex customer challenges, particularly in Kubernetes and GPU/GradientAI workloads, bridging deep support expertise with solutions architecture to design sophisticated cloud infrastructure. The engineer will also mentor junior staff, drive systemic technical improvements by partnering with Engineering, and participate in an operational on-call rotation for critical incidents.