Yogesh Bhandari
Technology Leader & Systems Architect
Co-Founder & CTO at CloudCheers. Former CTO at Gamemano and Veda Studios. Over a decade of hands-on experience across cloud infrastructure, distributed backends, and production AI architectures.
Building systems and engineering teams that hold up under pressure.
When traffic surges or a company scales past its first few hires, early architectural shortcuts turn into constant fires. I focus on building reliable platforms and repeatable engineering habits. That means setting up automated deployments, keeping cloud infrastructure simple to operate, and making sure the architecture matches where the business is heading.
Advising companies on backend modernization, cloud cost control, and production AI architectures that integrate cleanly into existing stacks.
Demonstrated Engineering Scale
Team Scale
Built and managed multi-disciplinary engineering departments across global operations.
Delivery Throughput
Accelerated software release cycles through automated CI/CD and modular architectures.
System Availability
Maintained fault-tolerant distributed infrastructure across multi-region Kubernetes clusters.
Commercial Systems
Delivered revenue-generating commercial platforms in fintech, clinical research, and gaming.
Architecture & Engineering Capabilities
How I evaluate technology choices: matching architecture to team capacity, infrastructure costs, and how fast the company actually needs to move.
Production AI & Retrieval Systems
Architecting reliable, cost-engineered AI features designed to integrate cleanly into existing software platforms.
- Retrieval-Augmented Generation (RAG) with hybrid lexical and vector search
- Model latency, token budgeting, and inference cost optimization
- Autonomous agentic workflows and tool-calling safety boundaries
- Local inference pipelines and secure on-premise model deployments
Cloud Infrastructure & Reliability
Designing automated, observable infrastructure that balances high availability with strict cost discipline.
- Zero-downtime migration from monolithic stacks to resilient microservices
- Infrastructure as Code (IaC) establishing repeatable multi-environment deployments
- Cloud cost audits eliminating wasted compute, egress, and storage spend
- Automated CI/CD delivery pipelines with integrated security checks
High-Concurrency Backends
Building low-latency distributed transaction systems capable of handling traffic spikes without degraded performance.
- High-throughput transactional APIs with asynchronous queue processing
- PostgreSQL indexing, query optimization, and read-replica partition topologies
- Event-driven architectures powered by Apache Kafka and Redis Pub/Sub
- Audit logging, permission boundaries, and regulatory data compliance
Engineering Leadership & Scaling
Translating business objectives into technical roadmaps that empower engineering teams to deliver reliably.
- Scaling engineering headcount from initial core team (40) to enterprise scale (100+)
- Standardizing code review guidelines, automated linting, and architectural review
- Pragmatic build-versus-buy decisions preventing proprietary vendor lock-in
- Direct stakeholder alignment connecting technical decisions with business outcomes
Leadership Experience & Track Record
A track record of building engineering organizations from the ground up, modernizing legacy systems, and leading high-stakes platform delivery.
Co-Founder & Chief Technology Officer
Advising growing companies on production AI deployments, cloud infrastructure cost optimization, and system reliability.
- Advising venture-backed startups and growing companies on sustainable AI architecture.
- Engineered cloud cost audit frameworks that reduced enterprise infrastructure spend.
- Conducting technical due diligence for executive leadership teams and investors.
Chief Technology Officer
Scaled the technology organization from 40 to 100+ engineers while supporting millions of concurrent platform events and real-time game state synchronization.
- Scaled engineering department from 40 to 100+ members across backend, infrastructure, mobile, and QA.
- Increased product delivery throughput by 50% through standardized GitOps and automated release rails.
- Reduced operational infrastructure expenditure by 20% while sustaining 99.95% platform uptime.
Chief Technology Officer
Built the core engineering department from the ground up into a 50+ person team delivering high-availability client architectures.
- Led microservices decomposition reducing overall time-to-market by 40% across client deliverables.
- Reduced infrastructure compute overhead by 35% through container right-sizing and caching layers.
- Tripled user traffic concurrency limits via database connection pooling and distributed Redis tiers.
Chief Operations Officer
Led the enterprise technology division with a 55-person engineering team delivering multi-tenant cloud platforms.
- Delivered 8+ production revenue-generating platforms for enterprise and institutional clients.
- Established foundational DevOps practices that cut project kickoff time by 70%.
- Instituted automated testing and delivery standards ensuring consistent, on-time milestones.
Python Team Lead
Led Python engineering in a regulated clinical research environment, delivering analytics platforms for clinical trial data.
- Architected Python clinical data visualization engines adhering to CDISC regulatory frameworks.
- Enhanced batch data processing throughput by 40% via optimized SQL execution plans and indexing.
- Managed cross-border remote development synchronizing US and Nepal time zones.
Evaluating an architectural overhaul or scaling an engineering team?
If you are rethinking your backend architecture, working to get cloud bills under control, or planning your first production AI feature, let's talk.