Vetted Engineering Professionals in the Greater Boston

Sahil Gupta

Screened ReferencesStrong rec.

Junior AI Software Engineer specializing in LLM agents, RAG, and healthcare NLP

MA, U.S.A1y exp

“Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.”

Priyanka Ramesh

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in Java/Spring Boot and React

Boston, MA2y exp

“Backend engineer (IpserLab) who owned Python services for a production quiz/analytics platform, focusing on reliability and low-latency behavior under peak load. Hands-on with Kubernetes + Docker deployments and GitHub Actions CI/CD in a GitOps-style workflow, including solving configuration drift and enabling fast rollbacks. Also implemented Kafka-based event streaming with idempotent consumers and strong observability (lag tracking, structured logging, alerting).”

Deva Sai Kumar Bheesetti

Screened

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

Lowell, MA5y exp

“JavaScript engineer who effectively "maintains" an internal open-source-style React/Node.js shared library used by multiple teams—owning API stability, semantic versioning, CI/testing, logging, and documentation. Demonstrates strong cross-team debugging and change-management skills (schema-driven refactors, feature flags, validation layers) to ship new features without breaking existing workflows, plus a profiling/benchmarking-driven approach to performance.”

Yang Qi

Screened

Mid-level Full-Stack Software Engineer specializing in AI platforms and data visualization

Cambridge, MA3y exp

“Full-stack engineer with healthcare/bioinformatics experience who built a real-time genomic data analysis and 2D visualization feature (React/TypeScript + D3, FastAPI) at University of Utah Health, deploying on AWS ECS Fargate with monitoring and measuring engagement via Google Analytics. Also built AWS Lambda-based ETL pipelines for lab data ingestion using pandas/NumPy with reliability patterns (idempotency, retries, CloudWatch alerting) and drove maintainability improvements through shared component libraries and React hooks.”

LAKSHMI KATTAMURI

Screened

Mid-level Embedded Software Engineer specializing in RTOS and microcontroller firmware

Boston, MA4y exp

“Backend/embedded-focused engineer with hands-on experience designing real-time, memory/power-constrained firmware architectures and also building Python/FastAPI services. Demonstrates strong production rigor across migrations (strangler pattern, shadow reads, feature flags), security (OIDC/JWT, RBAC/ABAC, Postgres RLS), and robustness for async workflows (idempotency, event ordering, state machines).”

“Robotics software engineer who built a ROS/C++ workcell stack to automate coating wooden panels with a 6-DOF arm, including trajectory generation, MoveIt/OMPL planning, and a single launch/config setup that runs in both Gazebo and on real hardware. Strong in debugging real-world planning failures (e.g., intermittent aborted/no-plan regions) through logging, planner swaps, and collision/kinematics tuning, and in designing modular ROS/ROS2 systems with versioned interfaces and translation layers for heterogeneous robots.”

“Full-stack AI engineer who built Skillmatch AI, an LLM/RAG-based job matching platform using FastAPI microservices, Airflow-orchestrated async pipelines, and Pinecone vector search (sub-second retrieval across 50k+ vectors) deployed on GCP with autoscaling. Also partnered directly with a cancer researcher to automate SEER + PubMed-driven report generation via an AI pipeline, emphasizing rapid prototyping and outcome-focused communication.”

“Gameplay/systems developer with shipped VR experience on Meta Quest (Litesport), owning a real-time workout scoring and progression system end-to-end including hit validation, HUD/UI, session state, and persistence. Known for event-driven architecture that decouples gameplay from UI, data-driven tunables for multiple modes, and rigorous VR performance work to hold 72 FPS using on-device profiling and debugging.”

“Game developer/designer with professional Unity experience and personal UE5/Godot projects, focused on improving player comprehension through subtle UX/environmental guidance. Has built end-to-end gameplay systems (FPS hitscan, health, saving/serialization, basic AI with A* and state machines) and shipped mobile titles on Google Play, including a physics-based trajectory/prediction feature that received positive feedback.”

Rasega Babu Kavitha

Screened

Mid-Level Full-Stack Software Engineer specializing in Java/Spring and React

Boston, MA4y exp

“Full-stack engineer who has shipped a real-time social engagement feature (live messaging + personalized feeds) for a career networking platform, owning everything from WebSockets/SSE and JWT+Redis auth through Docker/Kubernetes production deployment. Also built a production Flask backend for an AI-driven movie recommendation system on AWS, with strong API design (versioning/error standards) and hands-on performance tuning (Typesense +47% query improvement, Postgres indexing, Redis caching, CloudWatch-driven incident response).”

“Robotics simulation/localization engineer who built a lunar crater navigation stack in ROS/ROS2 and Gazebo, including custom localization/perception/planning packages. Demonstrated strong debugging skills by using tf2 frame analysis to fix camera-to-base_link alignment, cutting heading error from 75° to 0.48°, and handled large NASA lunar imagery (~4GB) by converting/downsampling data for Gazebo.”

“At Unar Labs, built and operationalized LLM capabilities inside a cloud-native SaaS product, emphasizing production reliability (fallbacks, observability, cost/latency/quality monitoring) and iterative improvement from user feedback. Also acts as a customer-facing technical lead—running developer demos/workshops and supporting sales through discovery, pilots/POCs, and technical walkthroughs to drive production adoption.”

“Backend/cloud engineer with hands-on ownership of a climate data extraction pipeline (BeautifulSoup + Pandas ETL + CRON) that automated 50k+ monthly data points and removed ~20 hours/week of manual work. Also built a multi-AZ Kubernetes deployment for a Node.js system using Terraform and GitHub Actions (blue-green, rollbacks) and has Kafka/FastAPI experience from a healthcare plan management project.”

Anudeep Reddy Veerla

Screened

Mid-Level Software Engineer specializing in cloud-native microservices

Boston, MA3y exp

“Built and shipped both a solo real-time multiplayer Spades game (TypeScript monorepo with shared client/server engine) and a production internal LLM-powered document Q&A tool for a SaaS company. Demonstrates strong RAG pipeline design (Pinecone + embeddings + reranking), rigorous eval/regression practices, and pragmatic data ingestion/observability work across Confluence, Notion, and messy PDFs/OCR—backed by clear metric improvements (P@1 61%→78%, escalations 40%→22%).”

Ronit Shetty

Screened

Entry-level Robotics Engineer specializing in SLAM, sensor fusion, and embedded avionics

Boston, MA1y exp

“Robotics software engineer focused on perception/SLAM and systems integration, recently built a quasi-dynamic mapping pipeline to track and reconstruct articulated objects (e.g., drawers) from RGB video using SAM2, COLMAP SfM, and 3D Gaussian Splatting. Also has strong ROS2 sensor-pipeline experience (custom messages, MCAP rosbag deserialization, tf2) and demonstrated real-time performance tuning by accelerating an ICP-based LiDAR SLAM component ~30x (from ~3s to <100ms per frame).”

“Built and shipped AI products at Humanitarians AI, including a full-stack multi-agent platform that consolidated six faculty AI tools into one interface and achieved 100+ user adoption, 70% less workflow switching, and a 6x latency improvement. Also designed a grounded document parser using FAISS and structured LLM outputs that reduced hallucinations by 60%, showing strong depth in both product-minded engineering and production AI systems.”

“Backend/full-stack engineer with experience spanning AI-powered fintech features and high-volume roadway surveillance/ALPR platforms. They have owned production APIs, improved API latency by 35% through database/query optimization, and helped drive a Kafka-based ingestion architecture that increased throughput by 30% while improving reliability at scale.”

Hammad Ur Rahman

Screened

Senior DevOps Engineer specializing in cloud infrastructure and CI/CD

Boston, Massachusetts11y exp

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

Shiva Dasi

Screened

Mid-level Software Engineer specializing in LLM agents and cloud-native systems

Boston, MA4y exp

“Built and shipped production LLM agents in compliance-sensitive environments (FERPA), emphasizing reliability via structured outputs, state-graph orchestration (LangGraph), and CI-driven eval/regression testing. Also has experience hardening messy ERP ingestion pipelines at scale (50K monthly orders) with normalization, idempotency/deduplication, and robust failure handling using AWS (SQS/CloudWatch) and PostgreSQL.”

“Frontend engineer with experience modernizing a large healthcare platform from Adobe Flex to React/TypeScript using micro frontends while keeping legacy systems live during migration. Brings strong performance tuning skills for data-heavy UIs and real-time map applications, including profiling-driven React optimization, Next.js SSR, and WebSocket-based live tracking.”

“Frontend engineer with 6 years of experience building AI-heavy React/TypeScript products, including an article summarization/report editor in Next.js, streaming chat interfaces, and a modular workflow tool for AI-generated video production. Stands out for diagnosing issues across the full stack—from React rendering and API payload design to Nginx streaming configuration—and for structuring maintainable frontend systems with multiple moving parts.”