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Vetted Kubernetes Professionals
Pre-screened and vetted.
Executive Technology & Resilience Leader specializing in AI, multi-cloud, SRE, and cyber resilience
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Senior Software Engineer specializing in frontend architecture and AI-enhanced developer tools
Senior Software Engineer specializing in cloud security and identity management
Senior Full-Stack & AI/ML Engineer specializing in cloud-native SaaS and IoT analytics
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Senior Cloud Engineer specializing in AWS/Azure infrastructure, DevOps, and cloud-native platforms
Principal/Staff Engineer specializing in platform architecture, AI/ML, and distributed systems
Mid-level systems researcher and engineer specializing in distributed storage and operating systems
Senior Software Engineer specializing in AI for Healthcare and Enterprise SaaS
Stephon Sands
Senior Enterprise Customer Success Leader specializing in Azure cloud adoption and renewals
“Enterprise cloud/SaaS customer success leader who owned a strategic $102M Azure commitment end-to-end, rescuing a Kubernetes migration by formalizing Sev A/B triage/escalation ownership and executive governance. Drove measurable outcomes including restored executive confidence and consumption growth from $1M to $2M/month (~30% adoption growth) by tying stabilization milestones to migration velocity, forecasting, and expansion strategy.”
Abhijay Sai Paladugu
Junior Data Scientist specializing in LLM agents, RAG, and reinforcement learning
“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”
Sai Chandra Bandi
Mid-level AI/ML Engineer specializing in Generative AI, LLM alignment, and RAG
“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”
Kanna Rajagopal
Executive Engineering Leader specializing in cloud services, distributed systems, and networking
“Amazon engineering leader (15+ years) targeting Senior Manager/Director roles, with deep ownership of contact-center latency and reliability initiatives. Shipped a global production improvement cutting call latency 30–40% and led a complex Citrix SDK integration, including incident response and a backward-compatible rollout strategy to protect existing customers while enabling new features.”
Kalyani Chittipolu
Mid-level Data Engineer specializing in AI/ML platforms and cloud data pipelines
“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”