Vetted Audit Logging Professionals

“Backend engineer who built a production retrieval-augmented narrative analysis platform for 100-page screenplays using a Node/Express orchestrator and a Python/FastAPI AI engine, including a key redesign from disk-based uploads to in-memory streaming to eliminate Windows file-lock failures. Also led a refactor of a municipal vehicle tracking system into a C-based distributed engine handling 4M+ daily packets with 99.99% data integrity and automation that reduced manual ops by 50%.”

Sriram Krishna

Screened

Mid-Level Software Engineer specializing in AI/ML and cloud-native platforms

Redmond, WA5y exp

“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”

“Data engineer with experience at Morgan Stanley and Star Health owning production-grade lakehouse pipelines for credit risk and healthcare datasets. Built Azure/Databricks/Delta/Snowflake-based platforms processing millions of records per day with strong data quality, observability (Monte Carlo/Azure Monitor), and reliability practices, plus experience delivering curated data services with performance tuning and backward-compatible versioning.”

Binaya Sharma

Screened

Senior Software Engineer specializing in full-stack systems, big data, and applied AI

Baton Rouge, LA6y exp

“Built and deployed ForensicLLM, a local domain-specific LLaMA-3.1-8B model for digital forensic investigators using RAFT + RAG over 1000+ curated research papers, with citation-aware responses and rigorous evaluation (BERTScore/G-Eval). Deployed via vLLM and Docker and validated through a chatbot survey with 80+ participants; published at DFRWS EU 2025.”

Bryant Conti

Screened

Junior Full-Stack Software Engineer specializing in React/Node.js and backend APIs

Los Angeles, CA4y exp

“Built and deployed a production Incident Tracking System using Next.js (App Router) + TypeScript with Postgres (Neon) and Prisma, including RBAC (User/Support/Admin), tickets/comments, and audit logging. Uses Zod for schema/type validation and relies on Chrome/React DevTools to debug and refine UI/UX and performance.”

“Gameplay/network engineer based in Argentina who has shipped across Unity and UE5, with standout work in deterministic simulation, authoritative multiplayer, and fully local AI-driven NPC systems. Particularly compelling for teams building systemic gameplay or real-time interactive experiences: they replaced Unity physics with a custom deterministic race pipeline, improved WebGL load performance, and later built an engine-agnostic local LLM/TTS/lip-sync stack for conversational NPCs.”

“AI/ML engineer with hands-on experience owning production deployments from discovery through post-launch stabilization, including real-time computer vision/OCR systems and LLM-powered RAG workflows. Stands out for translating messy customer workflows into reliable backend services, debugging non-deterministic retrieval issues, and hardening AI systems with validation, monitoring, and human-review fallbacks.”

Emma Choudhary

Screened

Senior Full-Stack Software Engineer specializing in Python, Django, and Generative AI

United States6y exp

“Backend/data engineer with hands-on production experience building partner-facing Python APIs (FastAPI, Celery, Postgres/Redis) and AWS serverless data platforms (Lambda, SQS, Step Functions, Glue). Emphasizes reliability and governance—JWT tenant-scoped auth, secrets/config hygiene, data-quality quarantine, and incident ownership—plus measurable SQL tuning that eliminated timeouts and stabilized reporting workloads.”

“Early-career automation/workflow builder who has owned small-scale end-to-end implementations (discovery through stabilization), using tools like Zapier, Google Sheets, and Airtable with strong validation and troubleshooting habits. Built and tested a production-style RAG application on AWS Bedrock (S3 + Knowledge Bases + embeddings + OpenSearch + retrieve-and-generate) with a Streamlit UI to deliver more grounded, context-aware document Q&A.”