Varun Singh

Backend & AI Infrastructure Engineer

Oracle SDE-1 · Go · Python · TypeScript · retrieval · agent orchestration · Go services

About

Backend and AI infrastructure engineer. I build retrieval systems, agent workflows, and the services underneath them — with a bias toward deterministic behavior, measurable performance, and production reliability. At Oracle I architected Composer, an AI workflow platform that turns 5G requirements into structured test plans and automation-ready bundles, and re-engineered the telemetry path behind it from 8 hours to 1.5. Outside work I build in the open: hybrid retrieval, Go concurrency primitives, and infrastructure tooling. Currently going deeper on inference serving — batching, routing, and GPU utilization.

SDE-1 @ Oracle · IIIT Jabalpur '25 · SIH 2023 national winner · Code for GovTech (C4GT)

Selected results

Experience

Associate Software Developer (SDE-1) — Oracle

Jul 2025—now · Hybrid

Architected Composer, an AI workflow platform that turns 5G requirements into structured test plans and automation-ready bundles — reducing manual authoring effort by 50% across 6+ network-function teams. Re-engineered Prometheus telemetry collection, cutting end-to-end data retrieval from 8 hours to 1.5. Led a backward-compatible migration from an overloaded log server to Artifactory.

  • Composer: intent-driven selection over 65k+ domain-organized JSON examples, versioned generation skills, deterministic validation, resumable finite-state workflows, immutable artifacts and approval gates — 50% less manual authoring across 6+ network-function teams.
  • Prometheus telemetry: packed PromQL requests, reusable HTTP sessions, retry handling and bounded dual-worker concurrency cut end-to-end retrieval from 8 hours to 1.5; a 23.9k-request benchmark measured 75.9% lower runtime and 99.4% fewer connection establishments.
  • Artifactory migration: backward-compatible move off an overloaded log server, with reusable upload abstractions and direct bastion-to-Artifactory transfers for Robot, network-function and OSO artifacts while preserving downstream paths; centralized Paramiko, JumpSSH and SFTP lifecycle cleanup to eliminate recurring SSH and file-descriptor leaks.

Project Intern — Oracle

Jan—Jun 2025 · Hybrid

Developed worker-utilization reporting for performance runs and refactored dashboard state management, cutting UI-related support tickets by 80% for 75+ engineers.

  • Worker-utilization reporting for performance runs, surfacing resource bottlenecks.
  • Refactored test-scheduling dashboard state management — 80% fewer UI-related support tickets for 75+ engineers.

Consulting Backend Engineer — Trijog

Feb—Apr 2024 · Remote

Owned end-to-end backend delivery for an LMS with 20k+ registered and 250+ peak concurrent users. Built the 7-module NestJS backend from scratch and engineered a Bull + FFmpeg pipeline that cut video readiness from 30 minutes to 5.

  • Built the 7-module NestJS backend from scratch with 3-role RBAC, Metabase reporting, async jobs and private DigitalOcean Spaces — 20k+ registered, 250+ peak concurrent users.
  • Bull + FFmpeg processing for 400+ videos with multipart uploads and 5 HLS renditions, cutting readiness from 30 minutes to 5; a Cloudflare Worker enforced signed, expiring auth on every manifest and segment.

Projects

repi

local-first log RCA · hybrid retrieval · resumable agent

An autonomous log-investigation engine for distributed systems. It clusters repetitive logs by signature, retrieves evidence with BM25 + pgvector/HNSW fused through Reciprocal Rank Fusion, and investigates root cause through an explicit, resumable state machine. Every step is persisted for auditability, and confidence is constrained server-side by the evidence actually cited. It can run fully locally with Ollama; hosted-model adapters are optional.

Stack: Python, Postgres, pgvector, ParadeDB, FastEmbed

  • implemented — Hybrid retrieval: ParadeDB BM25 + pgvector/HNSW fused with Reciprocal Rank Fusion.
  • implemented — Resumable investigation: a hand-rolled finite-state machine whose thoughts, actions and observations persist to Postgres, so a paused run resumes from stored state.
  • implemented — Deterministic server-side confidence gating that downgrades conclusions the cited evidence does not support.
  • measured — Docker image reduced from 5.58 GB to 1.12 GB by migrating embeddings to ONNX with FastEmbed.
  • measured — A 21-question retrieval suite plus scripted incident evaluations. This is a functional suite, not a published benchmark against a public dataset.
  • planned — Cross-encoder reranking and a vector-only / BM25-only / hybrid ablation. Neither exists in the code today.

github · demo

collapser-grpc

gRPC request collapsing · 82 ns/op dedupe hot path

An open-source Go sidecar for suppressing thundering-herd traffic. Equivalent unary requests share one backend call while followers wait for the same result. The proxy is schema-agnostic, uses detached backend execution so one cancelled caller cannot kill shared work, and exposes collapse, cache, inflight and backend-latency metrics through Prometheus.

Stack: Go, gRPC

  • benchmarked — 82 ns/op with zero allocations on the dedupe hot path. This is a Go microbenchmark of the in-process coordination path under synthetic high contention — it measures key hashing, cache lookup and in-flight map coordination only. It is NOT end-to-end RPC latency and contains no network, no serialization and no backend time.
  • benchmarked — Up to 1000:1 collapse ratio under synthetic 10k+ concurrent identical requests. Synthetic load, not a production traffic measurement.
  • implemented — Detached backend context, so a cancelled leader does not kill the shared call its followers are waiting on.
  • implemented — Schema-agnostic collapsing keyed by SHA256(method + payload) — no protobuf descriptors required.
  • implemented — Prometheus metrics for collapse ratio, cache hits, in-flight count and backend latency.
  • known limitation — Server-streaming RPCs currently return only the first response frame; client-streaming and bidirectional calls bypass collapsing entirely. Backend TLS uses the system trust store only — no mTLS, no custom CA bundles.
  • planned — Optional proto descriptors, mutual TLS, and per-method collapse policy. None of these are in the code today.

github

Fend

fleet-wide Linux hardening · Ansible + Electron

A desktop operator tool for applying repeatable Linux hardening across grouped Ubuntu hosts. Electron/React drives agentless Ansible playbooks over SSH, with key-based authentication and per-run audit logs. The project focuses on operationally legible, idempotent hardening rather than claiming full compliance with a security benchmark.

Stack: TypeScript, Electron, React, Ansible

  • implemented — Agentless, idempotent hardening: an Electron/React operator UI driving Ansible playbooks over key-based SSH against grouped Ubuntu inventories, with per-run logs.
  • known limitation — Ubuntu-only playbook paths, no central cross-operator audit trail, and coverage scoped to the implemented modules — it is not certified against CIS or any other benchmark.
  • planned — Benchmark mapping (CIS), dynamic inventory, in-app script editing, broader distro validation.

github

Skills

Languages

Go · Python · TypeScript · C++ · SQL

AI / LLM

Agent Orchestration · RAG · Hybrid Search (BM25 + Vector) · Reciprocal Rank Fusion · pgvector / HNSW · Retrieval Evaluation

Backend & Systems

FastAPI · Fastify · NestJS · PostgreSQL · Redis · gRPC · RabbitMQ · Bull · Prometheus

Infrastructure

Docker · Kubernetes · GitLab CI/CD · Artifactory · S3 · Cloudflare Workers · Helm

Achievements

Education

Indian Institute of Information Technology, Jabalpur — B.Tech, Computer Science and Engineering, Dec 2021—May 2025

Contact

Varun Singh

esc

Backend & AI Infrastructure Engineer

Oracle SDE-1 · Go · Python · TypeScript

retrieval · agent orchestration · Go services

ai · tool-calling assistant on the edge · 5 questions/day