Engineering support for complex, real-time platforms.

System architecture

Clear module boundaries, data contracts, and operational constraints.

• Domain modeling and bounded contexts
• API contracts and versioning strategy
• Service boundaries and ownership
• Risk register and technical roadmap

Backend engineering

Services and APIs built for predictable behavior under load.

• Node.js services (performance-focused)
• Postgres schema design and query tuning
• Idempotency, retries, and consistency patterns
• Authentication and authorization boundaries

Real-time systems

Event-driven flow and synchronization for systems that cannot drift.

• Pub/sub patterns and message contracts
• WebSocket patterns and backpressure
• Resync strategies and gap detection
• Ordering, deduplication, and replay

Frontend performance and UI architecture

Stable UI under frequent updates and dense data.

• State architecture to avoid render storms
• Virtualization and large list performance
• Data-fetching and caching strategy
• Component boundaries and reusability

Data flow and pipelines

Reliable ingestion, normalization, and metrics with clear ownership.

• Batch imports and validation rules
• Normalization layers and canonical models
• Metric computation with precision constraints
• Auditability and traceability

Reliability and observability

Instrumented systems you can operate with confidence.

• Structured logging and correlation IDs
• Health checks and SLO-minded metrics
• Error budgets and performance budgets
• Operational runbooks

Architecture-first

Constraints, interfaces, and boundaries are aligned before large implementation effort.

Incremental delivery

Working slices are shipped early to reduce risk and keep change controlled.

Operational discipline

Observability, failure modes, and performance budgets are treated as core deliverables.

Clean handoff

Decision logs and implementation documentation are delivered for team continuity.