Rishabh Pandey
I'm a software engineer on the core infrastructure team at Moveworks, building the platform layer the rest of the product runs on. Before that I was a production engineer at Meta, on the reliability of a distributed database tier powering an ads platform — observability, capacity, and incident response. Earlier: event pipelines and cloud infrastructure at Geico, and internships at Geico and Texas Instruments.
The problems that pull me in sit at the intersection of backend systems and applied AI — I've shipped LLM pipelines at Meta and agentic projects on the side, and I'm going deeper on both.
python
go
typescript
node
java
c/c++
sql
hack
docker
kubernetes
helm
terraform
github-actions
unix/linux
temporal
spark
airflow
gcp
fastapi
langchain
scikit-learn
vector search
eval / benchmarking
Moveworks — Software Engineer
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Meta — Production Engineer
Reliability of a distributed database tier powering an ads platform.
Owned the investigation that root-caused recurring database-throttling SEVs (~5–6 per half, ~30–40 unactioned alerts) to cross-team callers reusing shared functions and exhausting the owning team's QPS budget.
Instrumented per-callsite QPS observability via 70%/90% threshold detectors and method-signature attribution; designed and drove a callsite-forking remediation that segments ownership and isolates traffic per caller.
Built an applied ML pipeline on Llama 3.3 — structured summarization, embeddings, cosine-similarity clustering — grouping 8,000+ SEV follow-up tasks into actionable clusters for batch resolution.
Executed a subdomain migration to a dedicated tenant for a platform serving thousands of DAU; cut p95 latency 57% and shrank the fault-isolation domain.
Geico — Software Engineer
Serverless event pipelines and contact-center observability on AWS.
Authored Python Lambda services that normalize contact events, batch-write to DynamoDB, and fan out via EventBridge with DLQs and exponential backoff — 500–700K events/day at ~90% test coverage on least-privilege Terraform modules.
Rolled out Amazon Connect queue observability across 800+ queues with SNS + Slack alerting; cut batch metrics latency 12× (120 s → 10 s) via request coalescing and concurrent SDK fan-out.
Software Engineering Intern
Deployed JupyterHub on Azure Kubernetes Service with Azure AD SSO/RBAC and Spark/ADLS connectivity; the lake-first analytics workflow contributed to a ~25% reduction in team Snowflake spend.
Texas Instruments — SWE Intern
Internal tooling for licensing operations.
Engineered an Oracle APEX + PL/SQL internal tool that replaced a 4–6 hour manual lookup with a ~5-second self-serve flow, used daily by licensing ops across 250+ products.
Local Paste Service
repo ↗go
sqlite
launchd
A zero-dependency pastebin that lives entirely on your machine — a single 20 MB Go binary backed by SQLite in WAL mode for concurrent local storage. CLI-first workflow, automatic TTL expiration via a background garbage collector.
→ next: projects/interview-agent.mdLinkedIn Interview Agent
repo ↗fastapi
react
gpt-4o
faiss
An agentic RAG interview platform: ingests a job description and resume, maps skills semantically with FAISS, and generates adaptive questions conditioned on the candidate's gaps. Instrumented end to end — p50/p95 latency and $/session tracking, with question generation at ~2 s p95.
→ next: contact.jsonFull detail lives in the individual files — experience/ and projects/ in the tree.
Email is fastest. Happy to talk about infrastructure, reliability, infra tooling — or anything you've found on this site.