Résumé Bullets — pre-sorted by employer

Every bullet below is traceable to code in /srv. Nothing is inflated; where a number appears it came from a count or a written report, not an estimate.

The six that go on every version

• Designed and shipped an event-driven activity pipeline — transactional Postgres outbox → Kafka topic (6 partitions, keyed by actor) → three independent consumer groups materializing into Cassandra, Postgres, and a realtime channel — with at-least-once delivery deduplicated at each sink by a stable idempotency key.
• Built and operate a 26K-line Go realtime messaging service on Cassandra, Redis, and Kafka serving WebSocket chat, presence, push, and WebRTC signaling; contract-tested against both OpenAPI and AsyncAPI with a coverage test that fails the build on drift.
• Diagnosed and fixed a Cassandra phantom-partition defect in a geo-sharded ranking pipeline where upsert-on-write with an inferred partition key created one orphan row per user per region and leaked nameless records into production user feeds.
• Diagnosed and fixed a Redis Streams consumer-group leak in which unacknowledged failures accumulated 952 pending entries with no reclaim path; implemented aged-entry reclaim so failed work retries instead of being orphaned.
• Took a service from forgeable authentication to RS256 four-tier JWT verification with identity bound to the token, added 9 missing database tables, closed contract drift between client and server, and enforced all of it with the first CI the service ever had (typecheck, tests, end-to-end, contract diff).
• Trained a transformer language model from scratch in PyTorch (no HuggingFace) and built the platform around it: 9-gate evaluation as a promotion blocker, containerized streaming inference (SSE + WebSocket, continuous batching, KV cache), deployed on k3s + Helm with HPA scaling to 3 replicas under load; 86 % test coverage, load-tested at 198 requests / 0 failures / p95 2.7 s against a 6 s SLO.

For Google

Emphasis: scale reasoning, correctness, written design, Kubernetes, Go.

• Architected around a hard platform constraint — Cloudflare Workers cannot open raw TCP sockets, making Kafka and CQL permanently unreachable from the edge — by relocating the consumer tier to a host-resident Go service and connecting it through a transactional outbox rather than a dual write.
• Implemented hybrid feed fan-out (push below ~10k–50k followers, pull above) as a tuning constant rather than an architectural fork, with LexoRank fractional ordering so reordering one item does not rewrite every row after it.
• Authored three book-length engineering manuals (17–20 chapters, mermaid architecture diagrams) each ending in a numbered gap register and remediation roadmap; separated verified findings from inferred ones in dedicated documents.
• Located a fatal concurrent-map access in a Go WebRTC call path — an unrecoverable runtime error that terminates the process and drops every connection on the host — and documented it with a remediation entry rather than a retry wrapper.
• Deployed a multi-service Helm chart to k3s (inference, orchestrator, members, retrieval, search, NetworkPolicy, in-cluster MLflow) validated with kubectl apply --dry-run=server.

For Spotify

Emphasis: music domain, audio DSP, streaming, feeds, edge delivery.

• Built the music mode's activity graph: playlists, follows, feed, and posts as one event log with one materializer rather than four parallel pipelines, with system playlists as reserved-id rows and a single follows table discriminated by target_type.
• Implemented R2 multipart resumable upload (10 MiB equal parts, audio probe, Durable Object session coordination) and made TUS uploads genuinely resumable; made publishDraft atomic.
• Shipped audio fingerprint recognition: an FFT constellation matcher compiled to WebAssembly (kissfft.wasm) running inside a Cloudflare Durable Object, with an on-device Swift/vDSP counterpart in the iOS client.
• Built R2 range-request streaming for audio delivery at the edge, and a 10K-line, 65-route library/playlist/charts API over D1 and Postgres.
• Wrote a feature-by-feature parity analysis against Spotify scoring the system at 14 of 52, then burned the gap register down across ~60 numbered commits.
• Delivered the iOS music client: 128 files / 57.7K lines, with an AudioEngineActor isolating AVPlayer behind Swift structured concurrency.

For a bank / financial institution

Emphasis: correctness, auditability, contracts, fail-closed behavior, security.

• Built an ontology-driven financial exhibit pipeline (Palantir Foundry, Python Tier-2 transforms + React widget) with a data-driven normalizer registry per input shape, label-first reference qualification, and fail-closed ingest — an ambiguous case is WARN-blocked rather than silently producing a wrong exhibit.
• Made API contracts the enforced source of truth: OpenAPI/AsyncAPI plus 24 protobuf definitions generating Go, Swift, and TypeScript clients from one schema, with contract-diff and shadow-type gates in CI.
• Built the identity and authorization plane: ConnectRPC/gRPC gateway with RS256 token issuance and verification, ACL servicer, claims caching, entitlement mode-sync, and an auth event bus — asymmetric signing so verifiers never hold signing material.
• Implemented content moderation and DMCA compliance end to end: review-before-publication, report intake, decision queue, takedown, plus a three-way automated classifier in front of the human queue with its thresholds, costs, and documented limits — what the classifier cannot catch is written down.
• Conducted a full-platform security and architecture audit that identified dual backends serving one function, a three-way identity split, three parallel chat schema families, and credentials committed to a repository — each reported with location and remediation rather than quietly patched.

Numbers you can quote