--- title: "Work & experience — Samrat Mukherjee" description: "Full engineering history and project detail: Shortlistapp, Icebreakr, Stockpot, NetagiriFiles, Atum Labs and Defipe." url: "https://0xsamrat.com/work" author: "Samrat Mukherjee" updated: "2026-09-18" --- # Work & experience — Samrat Mukherjee > Every role and project, in full. AI Engineer · AI Agent Developer. ## Numbers - **88%** — autonomous answer coverage. A RAG rebuild of the answer layer at Shortlistapp raised how often the agent answers an employer's open-ended question on its own. - **28%** — lower LLM cost. Same rebuild — retrieving facts instead of re-prompting a large model per question. - **749** — tests on Stockpot. Including an adversarial suite against the agent's tool boundary. - **~15×** — fewer Redis commands. 2.6M → 173K per month, by replacing a polling scheduler with a Lua timer wheel. ## Projects ### Shortlistapp — An agent that applies to jobs end to end. 2026 · Live · paying customers · https://shortlistapp.co It reads the posting, fills the application, answers the employer's open-ended questions from the user's real background, and submits on real ATS portals. Headline metric: **88%** autonomous answer coverage - Stateful LangGraph workflow that resolves every field through tool calls and escalates rather than guessing. - RAG over each user's resume and history so answers come from real background — 88% autonomous answer coverage, 28% lower LLM cost. - A FactGuard layer blocks the model on any field with no retrieved fact, so it never fabricates on a submission the user cannot take back. - Idempotency keys and crash-safe replay guarantee no duplicate applications. Stack: Python, LangGraph, Pinecone, FastAPI, OpenTelemetry ### Icebreakr — AI outreach that researches a person before it writes. 2026 · Live on Chrome Web Store · https://useicebreakr.com Drafts personalized connection requests, DMs and cold emails using LLMs, behind a provider architecture with automatic fallback chains. Headline metric: **4-axis** LLM-as-judge eval harness - Plug-and-play provider architecture — Claude, OpenAI and Gemini behind interfaces with automatic fallback chains, swappable from a single config line. - Hardened against prompt injection: untrusted data isolated in delimiters so the model treats it as data, never instructions, with a typed-error retry loop. - Eval harness with deterministic auto-checks plus an LLM-as-judge scoring four subjective axes, using baseline/diff modes to catch prompt regressions before merge. - Go backend (Gin, PostgreSQL) with errgroup-orchestrated parallel fetches behind a 75s pipeline timeout, per-IP and per-user rate limiting, and daily usage caps. - Manifest V3 Chrome extension in TypeScript using a closed Shadow DOM overlay, with WorkOS OAuth/SSO and a signed handoff that never exposes tokens to JavaScript. Stack: Go, LLM, Next.js, Chrome MV3, TypeScript ### Stockpot — Agents that trade surplus food between restaurants. 2026 · Agentic Commerce Hackathon · https://getstockpot.shop Settling on real payment rails, where money moves only after delivery is verified. Headline metric: **749** tests, incl. adversarial suite - A hard LLM boundary: the matching engine is fully deterministic and agent tools accept no model-supplied numbers. The model chooses which check to run; Python computes every value. - Idempotent settlement protocol keyed on (listing, delivery) — the charge row is written pending before any network call, so a provider timeout retries instead of silently reporting success. - Card rails with network-enforced spending caps and partial capture: the buyer approves a ceiling once by passkey, and a charge above it is refused by the network. - Cut Redis command volume ~15× (2.6M → 173K/month) by replacing a polling scheduler with a Lua timer wheel that sleeps until the next deadline. Stack: Python, FastAPI, PostgreSQL, Redis Source: https://github.com/0xSamrat/stockpot ### NetagiriFiles — Civic transparency for ~800 Lok Sabha MPs. 2026 · 500+ monthly visitors · https://netagirifiles.fun Surfaces self-declared affidavit data with interactive D3.js charts, an India choropleth and per-MP profile pages. Headline metric: **<10 min** full dataset refresh - Concurrent Go ingestion pipeline (goroutines, token-bucket limiter) writing to Postgres via idempotent upserts, refreshing the full dataset in under 10 minutes. - Frontend in Next.js, React and Tailwind with per-MP profile pages indexed for search, serving 500+ monthly visitors. Stack: Go, Next.js, PostgreSQL, D3.js ## Professional experience ### AI Engineer & Founder — Shortlistapp.co (Remote) Jan 2026 – Present Live AI agent product with paying customers. The agent applies to jobs end to end — it reads the posting, fills the application, answers the employer's open-ended questions from the user's real background, and submits. - Built an autonomous job-application agent in Python (FastAPI, LangGraph) that plans and executes a full application as a stateful multi-step workflow, resolving each field through tool calls, recovering cleanly on step failure, and escalating to the user when it cannot proceed safely. - Built a RAG pipeline over each user's resume and history (embeddings + Pinecone) so open-ended employer questions are answered from the user's actual background instead of generated from scratch. This raised autonomous AI answer coverage 88% and cut LLM cost 28% by retrieving facts rather than re-prompting a large model per question. - Enforced a hard anti-hallucination boundary: a FactGuard layer blocks the model on any field with no retrieved fact, so the agent answers from real data or escalates. It never fabricates on a submission the user cannot take back. - Built the API layer with FastAPI and Pydantic, validating every model output against typed schemas so malformed LLM responses fail fast instead of reaching a live employer form. - Built the browser-automation engine that submits on real ATS portals (Greenhouse, Ashby, Lever), with idempotency keys and crash-safe replay guaranteeing no duplicate applications, plus anti-bot and CAPTCHA handling for reliable submission. - Instrumented the full agent path with LangSmith and OpenTelemetry, tracing every model call, tool invocation and decision, plus a queryable outcome taxonomy and dead-letter queue, so agent behavior is measurable and failures are debuggable. Stack: Python, FastAPI, Pydantic, LangGraph, LangSmith, Pinecone, RAG, OpenTelemetry, PostgreSQL, RabbitMQ, Docker, GitHub Actions ### Backend Engineer — Atum Labs (Atum Core) (Remote) Aug 2025 – Nov 2025 Intent-driven, multi-chain stablecoin clearing & settlement network letting payment providers move value across chains through one API. - Built core Go services for an intent-driven, auction-based settlement platform — payment gateway, solver gateway and on-chain verification — within a ~10-microservice system behind one REST API. - Built an off-chain quote-auction pipeline on Apache Kafka using per-source topics plus ephemeral per-request correlation topics with TTL-based cleanup, decoupling services into an event-driven flow. - Implemented a gRPC service (7 RPCs over Protocol Buffers) with a resumable server-streaming feed using monotonic sequence IDs, heartbeat liveness checks and replay-on-reconnect for reliable delivery across disconnects. - Architected an event-sourced PostgreSQL store with a race-free, two-phase work queue using SELECT FOR UPDATE SKIP LOCKED, giving crash-safe, idempotent settlement across a 20-worker pool. - Designed a write-only key-custody layer with a pluggable signing backend (encrypted storage plus GCP KMS / HashiCorp Vault / Fireblocks adapters), keeping private keys non-retrievable and signing isolated. - Containerized the service fleet with Docker, authored Kubernetes manifests and built GitHub Actions CI/CD promoting the exact staging-tested image to production by commit-SHA re-tag. Stack: Go, Kafka, gRPC, PostgreSQL, Docker, Kubernetes, GCP KMS ### Founder & Lead Backend Engineer — Defipe.io (Remote) Sep 2023 – May 2025 A derivatives trading protocol with a Go off-chain execution engine — order matching, position lifecycle, margin accounting and liquidation. - Architected a Go off-chain execution engine for a derivatives trading protocol from scratch, covering order matching, position lifecycle, margin accounting and liquidation logic. - Built a concurrent order-processing pipeline using goroutines for parallel matching and mutex-protected account state under simultaneous leverage constraints. - Implemented the liquidation engine and funding-rate mechanism; validated across 10K+ simulated leveraged trades with zero false liquidations in testing. - Built a low-latency WebSocket server propagating real-time state to 500+ concurrent users; grew to 500+ MAU and a 1,000+ member Discord, and won a $1,000 Soonami Venturethon grant. Stack: Go, WebSockets, Solidity, EVM ### Blockchain Developer — TechExactly (Kolkata, India) Feb 2022 – Nov 2022 NFT-marketplace smart contracts and the React frontend that drove them. - Engineered NFT-marketplace smart contracts with state-machine logic for ownership, settlement and transfer; built the React frontend with wallet connection and on-chain interactions. - Implemented gasless approvals (ERC-2612 permit), removing a separate approval transaction to cut onboarding friction and user gas costs. - Wrote test suites covering authorization, ownership transfer and failure paths to 95%+ functional coverage. Stack: Solidity, React, ERC-2612 ## Hackathons & achievements - **Soonami Venturethon (Cohort 5)** — Won a $1,000 grant for Defipe.io; grew it to 500+ testnet users and a 1,000+ member Discord. (https://app.foundance.org/projects/11247) - **ETHGlobal — Connext Pool Prize winner** — Cross-chain DAO governance with multichain proposal and voting execution. (https://ethglobal.com/showcase/ape-dao-2-0-i846k) - **ETH for ALL — Arcana Pool Prize winner** — Decentralized token swap via 0x Aggregator with social-login wallet onboarding. (https://devfolio.co/projects/defipe-b5ba) ## Technical skills - **AI Agents:** LangGraph, LangChain, agent orchestration, tool / function calling, multi-step workflows, browser-automation agents (computer use), multi-provider routing with fallbacks (Anthropic Claude, OpenAI, Gemini) - **RAG & Retrieval:** retrieval-augmented generation, embeddings, Pinecone, retrieval-quality evaluation (precision/recall@k, groundedness), grounded answer generation - **Evals, Safety & Observability:** LLM-as-judge evals, prompt-regression testing, prompt-injection defense, anti-hallucination guardrails, LangSmith, OpenTelemetry - **Python & APIs:** Python, FastAPI, Pydantic, async concurrency, REST APIs - **Backend & Distributed Systems:** Go (Golang), Kafka, RabbitMQ, gRPC, PostgreSQL, microservices, event-driven architecture, idempotency - **Infra & DevOps:** Docker, Kubernetes, GitHub Actions (CI/CD), GCP, AWS ## Education B.Tech, Electrical Engineering — B. P. Poddar Institute of Management and Technology, 2017 – 2021 ## Contact - Email: samrat.mukherjee2022@gmail.com - Book a 15-minute call: https://cal.com/0xsamrat/15min - Location: Bengaluru, India (Asia/Kolkata, UTC+5:30) - Availability: Open to work — full-time, remote-friendly - Resume (PDF): https://drive.google.com/file/d/14feSsx0a-vZ4A2sf8XZluPPLiVPx2DK_/view Reply time is same day, usually within a few hours. There is no contact form — email or the booking link are the two working paths.