Team development
Building teams through deliberate hiring, practical mentoring, clear ownership, and feedback grounded in the work.
About · Kamlesh Digarse
Engineering Leadership, Distributed Systems & Applied AI
I'm Kamlesh Digarse, an engineering leader with 18+ years of experience building software platforms, leading engineering teams, and solving complex technical challenges. My work spans cloud infrastructure, database observability, distributed systems, and emerging AI reliability technologies.
Professional background
Technical depth with organizational context.
My professional background combines hands-on systems thinking with engineering leadership. I focus on connecting architecture, product priorities, team ownership, and operational evidence so that complex platforms can evolve without losing reliability or clarity.
Current interests
- How engineering organizations make sound technical decisions under real delivery constraints.
- How distributed and database platforms expose useful reliability signals at scale.
- How AI-agent systems can be evaluated beyond infrastructure uptime and successful execution.
Career
Experience grounded in teams and operating systems.
February 2022 — August 2026
Engineering Manager · EDB
Led engineering work across database observability and platform capabilities, connecting product priorities with dependable delivery.
- — Built an observability engineering team
- — Worked on cloud and AI-related platform components
- — Led engineering teams responsible for platform capabilities
Earlier career entries are intentionally omitted until roles, employers, and dates are confirmed by the owner.
Leadership practice
Technical direction
Making architecture decisions with the engineers who will operate and evolve the system, not as a separate planning exercise.
Product partnership
Aligning product and engineering around outcomes, constraints, sequencing, and evidence instead of competing backlogs.
Operational excellence
Treating reliability, observability, and maintainability as product capabilities that require sustained ownership.
Technical expertise
Professional experience
Distributed Systems
- Event-driven architecture
- Kafka
- Scalability
- Multi-tenancy
- Reliability
Professional experience
Database & Observability
- PostgreSQL
- Database monitoring
- Metrics pipelines
- Cloud database services
- Performance engineering
Professional experience
Cloud & Platform Engineering
- AWS
- Kubernetes
- CI/CD
- Infrastructure architecture
Current research and building
AI Engineering & Research
- AI agent reliability
- LLM evaluation
- Agent execution tracing
- Failure pattern analysis
- AI observability
Engineering philosophy
Perspectives shaped by practice.
- 01
Engineering decisions should be driven by measurable outcomes.
- 02
Reliability is a product capability, not merely an operational metric.
- 03
Architecture should balance simplicity, scalability, and maintainability.
- 04
Strong engineering organizations require technical depth and people leadership.
- 05
AI systems require evaluation beyond infrastructure uptime.