Vetted Linux Professionals

Harshini Kanamathareddy

Screened ReferencesModerate rec.

Mid Software Engineer specializing in iOS, backend systems, and AI-powered applications

Hyderabad, India4y exp

“Full-stack/backend engineer with experience spanning React/TypeScript, Flask, Spring Boot, SQL databases, and production mobile optimization. They’ve shipped features end to end, improved query performance and app startup/crash metrics, and helped drive a configuration-driven architecture that enabled faster releases across 30 consumer applications.”

“Full-stack engineer with about 3 years of experience who is deeply hands-on with AI-assisted development and agentic systems. Built TubeAgent using LangChain, Ollama, FAISS, and Llama 3, and has demonstrated measurable impact by cutting review time by 90% and reducing deployment time from 30 minutes to under 5 minutes at NC State. Combines practical experimentation with strong architectural thinking around resilient, composable AI systems.”

“Built and owned core systems for VISTA, a VR drone training simulator in Unity/C#, including modular training scenarios, drone physics, restricted airspace logic, and dynamic weather-aware gameplay. Stands out for combining VR performance discipline on Meta Quest with realistic-yet-trainable flight controls and close collaboration with faculty SMEs to align the simulation with real training workflows.”

Bill Cheng

Screened ReferencesStrong rec.

Director-level Engineering Leader specializing in SaaS platforms and AI systems

Remote, USA26y exp

“Entrepreneurial candidate building an LLC focused on applying AI to improve call center customer service, with an early go-to-market focus on local government call centers. They are already in discussions with a government prospect and have a clear thesis around solving high turnover and low knowledge retention through AI-assisted training and support systems.”

“Graduate robotics engineer from Boston University who led development of a perception-to-decision pipeline for a multi-robot, perception-driven navigation and coordination system. Strong in ROS/ROS2 C++ on Linux, with hands-on experience hardening real-time behavior on hardware (timing sync, QoS/queue/executor tuning) and validating via Gazebo/Webots plus real-robot testing; also uses Docker and basic CI for regression checks.”

“Built and shipped a production LLM-powered grading platform that automates rubric-aligned scoring and feedback, with strong guardrails (RAG grounding, structured JSON, validation/retries) and operational rigor (metrics, drift monitoring). Experienced using CrewAI to orchestrate multi-agent workflows end-to-end and validating quality via gold-set benchmarking against human graders with regression testing on every prompt/model change.”

“Built a production SQL chatbot for access-log analytics that replaced manual custom report requests with natural-language querying, using LangGraph and a ChromaDB-backed RAG pipeline for grounded, consistent answers. Implemented a privacy-preserving design where the LLM never sees raw customer data (only query metadata) and has experience building multi-agent/tool-calling systems with LangGraph (DeepAgents), including solving sub-agent communication drift via self-reflection.”

“Robotics/embedded engineer who built core firmware for an autonomous underwater vehicle (AUV) used to detect wreckage in shallow coastal waters, including propulsion control, sonar/magnetometer processing, and low-frequency magnetic underwater comms. Demonstrated strong real-time systems skills by redesigning a noisy comms protocol (checksums/retries) and implementing a lightweight scheduler to stabilize heading control, plus ROS 2 sensor/control integration with tf2 and simulation/CI tooling.”

“University hackathon finalist (2nd place) who built CareerSpark, a production-style multi-agent career guidance app in 24 hours using a hierarchical debate architecture with a moderator/judge agent. Has startup internship experience at LiveSpheres AI using LangChain for multi-LLM orchestration, and demonstrates a structured approach to testing/evaluation (golden sets, integration sims, latency/accuracy KPIs) plus strong non-technical stakeholder communication.”

“Built a secure, on-prem/private GPT assistant to replace manual SharePoint-style search across thousands of policies/SOPs/engineering docs, using a production RAG stack (LangChain/LangGraph, FAISS/Chroma, PyMuPDF+OCR, vLLM). Implemented layout-aware ingestion (including table-to-JSON) and a multi-agent retrieval/generation/verification workflow with strong observability and compliance guardrails, delivering ~70% reduction in search time.”

“Built and deployed an end-to-end product that brings a research-paper approach into production for large-scale time-series clustering, with attention to partitioning, latency, and scalability. Also designed a Python-based backend validation service (comparing outputs to database ground truths) and handled production reliability issues by reproducing dataset-specific crashes and hardening corner-case behavior with client-friendly errors.”

“Cloud/DevOps engineer (6+ years) with healthcare domain experience who has owned production AWS systems end-to-end—building real-time data pipelines and an admission forecasting ML service delivered via API and Tableau. Led EMR modernization from on-prem/VMs to containerized AWS using phased migration and blue-green deployments, achieving ~99.5% uptime while cutting on-prem footprint ~30% and driving major automation gains (up to ~90% manual work reduction).”

“Serial entrepreneur since leaving corporate in 2009, working largely for equity on multiple startups. Building (1) academically rigorous, anti-overfitting quant/backtesting tools for retail investors (with potential applicability to smaller hedge funds lacking quant staff) and (2) a partner-led “social-as-a-service” platform for verticals like real estate/PropTech (including FSBO use cases) focused on first-party data capture vs. big tech.”

“Data engineer focused on AWS-based enterprise data platforms, owning end-to-end pipelines from multi-source batch/stream ingestion (Glue/Kinesis/StreamSets/Airflow) through PySpark transformations into curated datasets for Redshift/Snowflake. Emphasizes production reliability with strong monitoring/observability and data quality gates, and reports ~30% performance improvement plus improved SLAs and latency after optimization.”

“QA professional focused on CRM workflow and case management releases, owning end-to-end validation from staging through release readiness. Demonstrated ability to catch critical UI-to-backend mapping defects early using API/DB validation and audit logs, then prevent recurrence by adding automated edge-case tests into CI.”

Apurva Banka

Screened

Mid-level Full-Stack & AI Engineer specializing in cloud, data platforms, and LLM automation

Houston, TX5y exp

“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”

vineetha Pulipati

Screened

Mid-level Software Engineer specializing in backend microservices and cloud data pipelines

MO, USA4y exp

“Backend engineer with Morgan Stanley experience building and owning an end-to-end Python FastAPI microservice for high-volume market data used by trading and risk systems. Strong in performance tuning and reliability (PySpark, Redis caching, async APIs), real-time streaming with Kafka, and production operations (Docker/Kubernetes, GitOps-style CI/CD, monitoring). Has led cloud/on-prem migration work across AWS and Azure, including fixing Azure Synapse performance issues via query and pipeline redesign.”

Abhishek Saraswat

Screened

Mid-level Software Engineer specializing in Java backend microservices

Arlington, TX4y exp

“Backend/distributed-systems engineer focused on automation and near-real-time processing, building Java/Spring Boot microservices with Kafka, PostgreSQL, and AWS. Strong in scaling and reliability work—debugging tricky asynchronous messaging issues (delays, duplicates, out-of-order events) and improving resilience/observability with retries, fallbacks, logging, and monitoring. No production ROS/ROS2 experience yet, but has studied core ROS concepts and draws clear parallels to event-driven architectures.”