Vetted Shell Scripting Professionals

“Data engineer who has owned production pipelines end-to-end—from Kafka/Airflow ingestion through SQL/Python validation and dbt transformations into Redshift/BI. Also built and operated a large-scale distributed web scraping platform (50–100 sites daily, ~5–10M records/day) with Kubernetes, Kafka queues, robust retries/DLQ, anti-bot measures, and backfill-safe raw HTML storage.”

Nidhi Sura

Screened

Junior Software Engineer specializing in AI platforms, distributed systems, and cloud infrastructure

Dublin, CA1y exp

“Software engineer with limited robotics background but deep experience building end-to-end document ingestion and image understanding systems, including a CAD-specific pipeline using a custom model to extract components and bounding boxes for user-facing visualization and Q&A. Also brings strong infrastructure/DevOps skills (Docker, Kubernetes, GitHub Actions, Terraform) with emphasis on reliability, cost optimization, and uptime.”

“Senior engineer with experience at Micro Focus/HPE (now OpenText) supporting enterprise customers on monitoring platform deployments, upgrades, and ongoing product use. Brings hands-on expertise in operations agents, agentless integrations, security-related upgrade troubleshooting, and cross-functional escalation with engineering to keep customer environments stable and successful.”

“Full-stack product engineer with strong web3/blockchain experience, having built invoicing/tokenization, transaction explorer, and no-code workflow products across React, Node.js/serverless, and SQL. Stands out for combining deep technical execution with product thinking—improving onboarding completion by ~40%, shipping quickly under ambiguity, and creating reusable platform primitives for auditability and multi-tenant customization.”

Keeravani Chekuri

Screened

Mid-level AI/ML Engineer specializing in LLM systems and MLOps

Boston, MA3y exp

“Built and deployed an AI tutoring assistant end-to-end at Nexora School, spanning discovery with school districts, multi-agent LangGraph/RAG architecture, AWS Bedrock migration, and post-launch stabilization. Stands out for combining hands-on LLM systems engineering with strong educator-facing trust building, FERPA-driven architecture decisions, and disciplined production practices around evals, logging, and messy document ingestion.”

“Backend engineer experienced in evolving high-scale legacy on-prem systems into cloud-native, event-driven microservices on AWS/Kubernetes (noted peak traffic ~1.5M QPS). Strong focus on reliability engineering and operational excellence—SLO-driven observability, GitOps/canary rollouts, chaos testing, and preventing cascading failures (e.g., retry-storm mitigation).”

“Built and deployed “ApartmentFinder AI,” a multi-agent system using Google ADK, Gemini, and Google Maps MCP to automate apartment shortlisting and commute-time analysis, cutting a 45–70 minute user workflow down to ~30 seconds. Also has strong delivery/process chops from serving as an SDLC Release Coordinator, managing 52+ releases and reducing SDLC issues by 84%.”

“Backend/infra-focused engineer who owned production systems for distributed ML experimentation (hyperparameter tuning across a cluster with GPU scaling, custom scheduling, and checkpoint-based fault tolerance). Also built and operated a low-latency log validation service using queued async workflows with idempotency, retries/backoff, and strong observability, plus experience building resilient Selenium-based browser automations for complex multi-step web flows.”

Anita Bhagashetti

Screened

Mid-Level Software Engineer specializing in distributed systems and cloud microservices

3y exp

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”

Md Abul Kalam Azad

Screened

Director-level Software Development Leader specializing in FinTech, Blockchain, and AI

Kuala Lumpur, Malaysia24y exp

“Bootstrapped founder with a technical background who has already built an MVP SaaS loyalty and referral platform plus a tablet/mobile POS companion product, leveraging Azure and Google Cloud support rather than outside capital. Focused on learning-by-building, resource-efficient execution, and forming highly motivated, equity-aligned teams.”

“Engineer with hands-on experience building adaptive assessment and LMS-style platforms across React/TypeScript, edge/serverless backends, and Postgres, with strong evidence of cross-layer debugging and performance optimization. Also brings ML product experience from a small-team internship, where they shipped a CatBoost-powered investor demo under ambiguity and created reusable inference infrastructure.”

RAUNAQ BEDI

Screened

Entry-level Software Engineer specializing in AI, data engineering, and cloud DevOps

San Francisco, CA1y exp

“Product-minded full-stack engineer with strong React/TypeScript, serverless AWS, and Postgres depth, highlighted by owning real-time personalization and onboarding experiences at mParticle. Stands out for combining deep performance debugging with measurable product impact—improving activation by 28%, reducing time-to-insights by 35%, and building reusable internal platform primitives adopted by 12 teams.”