Senior software engineer helping Talview ship reliable hiring platforms, smoother reviewer tools, and calmer releases.
|
**Modular reviewer surface**
_Turning the reviewer UI into an extensible platform other squads can plug into safely._ |
**Service migrations**
_Splitting a monolith into event-driven services with shared contracts and tooling._ |
**Delivery guardrails**
_Feature flags, automated runbooks, and SLO burn alerts so weekly releases stay boring._ |
| Metric | Value |
|---|---|
| Services in prod | 28+ |
| Deploy cadence | 8-12/wk |
| Change failure | <3% |
| Rollback time | 12 min |
| Error budget | <20% |
| Ops coverage | Follow-the-sun |
- Platforms over projects: Broke a feature team mindset by building shared reviewer components and API contracts.
- Deploys with receipts: Feature flags, preview envs, and release scorecards became required before flipping toggles.
- Incident calm: Introduced SLO burn alerts, templated RCAs, and automated dashboards so on-call has context.
- Mentor-mode: Pairing hours + architecture office hours raise the floor for new hires and interns.
🔥 Open Source Spotlight — blocknote-py
Convert BlockNote.js blocks to HTML, Markdown, PDF, or JSON using type-safe Pydantic models. Perfect for FastAPI, Django, or Flask backends that need rich text on the server.
| Why it helps | What you get |
|---|---|
| Server-side BlockNote support without Node.js. Typed models keep payloads safe and easy to validate. | • HTML/Markdown/PDF converters with styling preserved • 95%+ test coverage, CI, and docs • Optional extras pull in doc + PDF tooling only when needed |
| Period | Role |
|---|---|
| 2025 → Now | Senior Software Engineer · Talview Leading platform work for reviewer tooling, observability, and deployment frameworks across squads. |
| 2023 → 2025 | Software Engineer · Talview Shipped event-driven services, integrations, and delivery tooling; championed feature flags and incident hygiene. |
| Jan 2023 → May 2023 | Engineering Intern → Associate SWE · Talview Delivered Slack automation, tracing rollouts, and GraphQL migrations; documented playbooks for the next cohort. |
| Area | Everyday Tools |
|---|---|
| 🧱 Platform & services | Python, Node.js/TypeScript, FastAPI, Nest, Kafka, Temporal, REST + GraphQL |
| 🚀 Delivery & DevEx | Monorepos, NX/Turborepo, feature flags, CI/CD (Actions, Argo), IaC |
| ☁️ Cloud & ops | AWS (Lambda, ECS, EC2, S3, SQS/SNS), Azure Blob, Docker, Kubernetes, Terraform |
| 🗄 Storage & data | PostgreSQL, Redis, DynamoDB, Firebase, object storage |
| 📈 Observability | OpenTelemetry, Prometheus, Grafana, Sentry, structured logs |
| 🤝 Collaboration | RFCs, design reviews, incident command, customer handoffs, compliance-ready workflows |
- Communicate early: Short updates, dashboards, and runbooks keep everyone in the loop.
- Ship small, then harden: Feature flags first, then tests + docs.
- Measure everything: Latency, quality, and on-call noise decide what we fix next.
- Automate recovery: Bots and scripts fix the obvious incidents before humans wake up.
- Partner with AI copilots: Codex, Claude Code, and similar tools help plan tasks, juggle worktrees, and accelerate delivery while keeping human review in charge.
If you're wrestling with a migration, a release pipeline, or an observability gap, I'm probably debugging the same thing—reach out.
