Vetted Operating Systems Professionals

Ishwari Kulkarni

Screened

Intern IT & Data Analytics professional specializing in automation, cloud operations, and dashboards

Dallas, TX2y exp

“AppSec-focused engineer with experience spanning Accenture and a digital operations support internship, emphasizing secure SDLC and CI/CD security automation (SAST/DAST/SCA). Has hands-on troubleshooting experience using logs/metrics/APM traces (e.g., resolving DAST timeouts caused by rate limiting) and designs AWS/Kubernetes scanning integrations with least-privilege IAM, private networking, secrets management, and observability.”

“Master’s CS candidate with backend internship experience modernizing live operational workflows at NatWest/NetWess, focusing on reliability improvements, safer CI/CD deployments, and incremental refactors using feature flags and rollback paths. Built FastAPI-based APIs with strong security patterns (JWT + 2FA/TOTP, centralized authorization, RLS) and demonstrated attention to edge cases like idempotency and data consistency in a Netflix-clone project.”

“Robotics software engineer focused on ROS 2 localization/SLAM: built a particle-filter (Monte Carlo) localization system in Python with likelihood-field modeling to handle noisy LiDAR and dynamic environments. Strong in debugging ROS 2 integration issues (tf2 frame sync, DDS/QoS message reliability) and in profiling/optimizing pipelines to reach real-time performance (~10 Hz) using precomputation and KD-trees.”

“Unity/VR developer and PhD researcher who served as lead developer on a clinical VR application (VheaRts) used by surgeons at Great Ormond Street Hospital, taking over a messy codebase and rebuilding its architecture, documentation, and extensibility. Also built research-focused Unity VR experiments (e.g., change blindness in a dynamic living room) with sophisticated logic to control participant attention while monitoring physiological cues.”

“Software engineer with production experience building a serverless monolith and multi-layer video pipeline at easyML, plus hands-on integration of multiple LLM providers (Grok/Claude/OpenAI) into a full-stack app. Interested in robotics via computer vision (OpenCV/OpenMMLab), with a strong real-time systems mindset around SLOs, latency, determinism, and reliability; also has low-level OS experience writing a keyboard device driver.”

“Backend engineer with experience at Roche and Jarsy focused on API and data-layer performance. Re-architected slow generalized endpoints into more efficient APIs (30% faster lookups) and led a schema refactor/migration with feature-flag rollout, dual writes, rollback scripts, and automated integrity checks; also addressed pipeline duplicate-entry issues via deduplication.”

Prachika Agarwal

Screened

Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation

New York, NY4y exp

“Software engineer who built and scaled an internal automation/auditing tool for analyzing Google and Adobe tagging containers, adopted by 13 internal clients and saving ~15 hours per audit. Has experience shipping containerized, Kubernetes-orchestrated systems and integrating OpenAI APIs into an agentic chatbot feature (plus prior NLP chatbot work during a Cyber Peace Foundation internship).”

Ti Wu

Screened

Junior Full-Stack Developer specializing in web apps and reinforcement learning

Hsinchu, Taiwan1y exp

“Built an AI basketball shooting coach that analyzes player form against NBA players and recruited 30+ beta users via Reddit to drive iterative UI/workflow improvements. Also has internship experience building an administrative server and coordinating API/database compatibility with another client server, emphasizing communication and integration quality.”

“Built production LLM agents at Hivenue and Amazon, spanning consumer booking automation and internal data-query/reporting workflows. Stands out for combining conversational UX with strong reliability engineering—strict tool use, state machines, schema validation, idempotency, and evaluation pipelines—and can point to measurable impact including a 21% reduction in time to book and a 12% conversion lift.”

“Built an LLM-powered customer segmentation agent during a Chewy internship, consolidating Snowflake data into a knowledge graph so non-technical marketing users could query customer cohorts in natural language. Stands out for combining agent/tooling design with rigorous data engineering practices, including schema audits, imputation, validation layers, and idempotent pipelines on messy large-scale datasets.”

“Backend/AI infrastructure engineer focused on production-ready LLM systems and distributed workflows. They described building a RAG-based multi-step agent with strong reliability controls, evaluation loops, and graceful degradation that improved latency by 30%, retrieval accuracy by 15%, and reduced support workload by 40%.”

“Worked at AMD on Vivado tool releases, focusing on adding and integrating new IP/SoC functionality into the Vivado flow and validating expected behavior through testing. Comfortable engaging with customers and open to travel for hands-on customer-facing work.”

“Built an autonomous decision analytics LLM agent for end-to-end tabular binary classification, using RAG (FAISS) to retain context across multi-step queries. Deployed as a FastAPI service with production-style reliability features (schema-aware validation, fallbacks, retries, structured outputs) plus offline/online evaluation and monitoring to reduce analysis time and improve consistency versus stateless approaches.”

Mukul Sai Pendem

Screened

Mid-level Full-Stack Engineer specializing in cloud-native microservices and DevOps

United States (Remote)4y exp

“Backend engineer with strong Python/FastAPI microservices ownership, including an ML-serving service with embeddings, async DB access, and Redis caching to reduce latency under high load. Experienced deploying and operating containerized services on Kubernetes using GitOps (Argo CD/Helm) with automated CI/CD, plus hands-on Kafka streaming pipeline tuning and enterprise migration work (Infosys) using blue-green/active-passive strategies.”

Kavya Aitagoni

Screened

Junior Full-Stack Engineer specializing in web platforms and live events

San Francisco, CA2y exp

“Full-stack product engineer with experience shipping user-facing web products end-to-end, including an event analytics dashboard and checkout improvements at Eventbrite. Stands out for combining frontend polish, backend reliability, and production-minded practices like idempotent APIs, query optimization, CI/CD, logging, and monitoring to improve conversion and reduce engineering dependency.”

Rohit Vibhu Channananjundarya

Screened

Mid-level Software Engineer specializing in distributed systems and full-stack platforms

Chicago, IL6y exp

“Engineer who treats AI as a force multiplier rather than a replacement for judgment, with hands-on experience using tools like Claude Code, Cursor, Copilot, and Codex across planning, coding, testing, and review. Particularly notable for building a multi-agent PR review system that automated summarization, risk scanning, schema validation, and test suggestions, helping the team shift reviewer time toward architecture and business logic.”

Hilary Lutz

Screened

Intern IT and cybersecurity professional with data and Python skills

Philadelphia, PA5y exp

“Internship experience at Arkema and Proscia focused on improving onboarding and internal automation workflows. Built SQL-based processes for computer onboarding and security compliance checks, redesigned cybersecurity onboarding for different departments, and created templated setup instructions with GitHub-based review safeguards.”

“Full-stack product engineer with hands-on experience building a React/serverless/SQL e-commerce platform for Haagen-Dazs and improving consumer UX in a location-based animal discovery app. Stands out for pairing strong technical fundamentals—component architecture, SQL performance tuning, reusable primitives—with measurable product outcomes like 40% more completed orders, 25% customer growth, 95% navigation accuracy, and 20% fewer device malfunctions.”

Yash Priyadarshi

Screened

Junior Software Engineer specializing in distributed systems and cloud infrastructure

Bengaluru, India2y exp

“Backend/distributed-systems engineer who built a Golang distributed key-value store on AWS using Multi-Paxos, WAL, and non-blocking gRPC replication (cutting write latency ~40%) and proactively addressed tricky failure modes like leader-election livelock. Also developed a Python/Kubernetes cost-optimization scaling engine deployed with Helm/Terraform, delivering ~$40K annual savings while sustaining 99.99% uptime, and drives contract-first API development (OpenAPI/Swagger) to speed frontend integration.”

“Early-career candidate with a thoughtful, engineering-first approach to AI-assisted development: they use AI to accelerate implementation while retaining human ownership of architecture and final code quality. They recently built a speech-to-text workflow using Groq Whisper and showed practical judgment by designing around imperfect transcription accuracy with checks and fallback handling.”

“Frontend-focused builder who developed Lushgreen, an ML-powered harvest forecasting and recommendation platform for farmers, agricultural businesses, and home gardeners. Stands out for combining React UI engineering, performance optimization, and user-centered simplification of complex ML outputs for non-technical users.”

“Developer with experience across Drupal and Java/Spring Boot applications using React/jQuery for UI and API-driven features. Has handled production issues by tuning reverse proxy timeouts for login problems and troubleshooting data pipeline inaccuracies by fixing database queries, with a focus on performance and careful verification before changes.”

“Backend/ML engineer working on a battery energy storage system operations dashboard: built a Flask backend integrated with OAuth and a separate FastAPI optimization/simulation service, deployed via Docker CI/CD to Azure Container Apps. Strong in productionizing ML (AzureML to batch endpoints) and in performance/scalability patterns (Postgres indexing/JSONB, per-unit data isolation, async throttling + caching for year-long CPU-intensive simulations across 40+ scenarios).”

Harini Vinu

Screened

Intern Software Engineer specializing in cloud, big data, and test automation

New York, United States1y exp

“Internship experience at Qualitest building and deploying an LLM-powered test automation system that reduced manual test creation and improved efficiency (~40%). Demonstrates strong production engineering for LLM systems (timeouts/retries/monitoring/caching, prompt optimization, batching) and has scaled workflows to 100+ concurrent jobs; also has orchestration experience with AWS Step Functions and Kubernetes.”