Vetted Scrum Professionals

Akhila Chitturi

Screened

Mid-level Embedded Software Engineer specializing in real-time control and automated testing

Detroit, MI3y exp

“Master’s thesis researcher building an intelligent fault diagnosis and predictive maintenance stack for autonomous quadcopters—covering simulation-based fault injection, signal processing (Id/Iq), ML fault classification, and real-time edge deployment on Raspberry Pi with Hailo-8 acceleration. Previously delivered production C++ middleware/microservices at Accolite and has hands-on experience with constrained networking via a LoRaWAN IoT communication stack.”

Renaud THIERRY

Screened

Senior Unity 3D Developer specializing in mobile games and AR applications

Grenoble, France11y exp

“Unity developer who improved the feel and usability of a text-heavy game by implementing satisfying UI scrolling and adding keyboard-based navigation, earning positive feedback from both the dev team and users. Also has professional client/server experience (REST) and contributed to a Unity industrial application for AI-managed smart-home/domotics control, leveraging Agile/Jira and AI coding assistants to boost delivery.”

Tracy Nguyen

Screened

Mid-Level Software Engineer specializing in Front-End Web Development

Toronto, Canada3y exp

“Frontend engineer with React + TypeScript experience building internal dashboards and a nonprofit festival website delivered end-to-end in 6 weeks. Emphasizes scalable quality practices (documentation ownership, code reviews, CI/CD, testing) and user-centered delivery, including accessibility, multilingual support, and enabling non-technical stakeholders to update content.”

“Full-stack product engineer in a high-growth startup environment who led a revenue- and retention-driving Loyalty Pass feature end-to-end using Next.js App Router, TypeScript, and Postgres. They pair strong frontend performance instincts with backend reliability work, including Stripe-based onboarding/billing refactors, idempotent workflows, and production observability.”

“Unity/C# engineer with hands-on ownership of a server-backed resource loading pipeline that kept build size small, preserved UI responsiveness via parallel services, and handled dynamic asset replacement with ghost objects and memory cleanup. Also brings a pragmatic, architecture-first approach to AI/LLM integration, emphasizing provider abstraction, testing, cost control, and guardrails for hallucinations.”

Meghana Divve

Screened

Mid-level Full-Stack Software Engineer specializing in cloud-native enterprise applications

Tampa, FL6y exp

“Built and launched a production internal AI support assistant at CompuCom, focused on reducing time spent searching across systems by combining retrieval, internal tool use, and grounded LLM responses. Stands out for pragmatic zero-to-one execution: scoped the product in phases, prioritized safety over premature autonomy, and iterated using real user feedback to improve relevance, usability, latency, and cost.”

“Outbound-focused sales candidate with experience spanning SaaS-style prospecting at ShineCo and customer-facing consultative selling at Madrasi Chai. Stands out for highly personalized, insight-led outreach into higher education and wellness organizations, including generating 10+ qualified leads per month and turning cold, initially resistant stakeholders into meetings through research-backed messaging.”

Ganapathi Deivanayagam

Screened

Intern Full-Stack Developer specializing in web applications and data pipelines

Milledgeville, GA0y exp

“New-grad full-stack developer with strong self-directed project work spanning collaborative web apps, AI-assisted CRM features, and LLM-supported thesis development. Particularly notable for combining modern web tooling, real-time collaboration, and pragmatic AI usage while also showing initiative in ambiguous research environments by automating manual ETL work with Python and OCR.”

“Product leader with hands-on experience building enterprise SaaS products from 0 to 1, including Valueflow, a customer lifecycle mapping platform shipped as an MVP in 6 months. Also brings applied AI product experience in compliance software, launching an LLM-based document validation workflow with human-in-the-loop review and strong cross-functional alignment across regulatory, engineering, design, and customer-facing teams.”

“Backend-leaning engineer who has significantly owned the architecture behind complex browser-based internal analytics dashboards for enterprise operations teams. Stands out for connecting Python/FastAPI/Django backend design, async processing, PostgreSQL optimization, and browser performance improvements to make real-time monitoring UIs faster and more usable.”

“Backend engineer with research and industry experience building data-intensive systems for healthcare and IoT. Built Python/Flask/FastAPI services with real-time ingestion and ETL into relational databases, emphasizing data quality, performance tuning, and secure access controls (JWT, RBAC, row-level filtering). Notably caught hardware-driven sensor anomalies others missed and implemented quarantine/alerting to prevent bad data from corrupting analytics.”

“AI/LLM engineer who has shipped production RAG chatbots using LangChain/OpenAI with FAISS and FastAPI, focusing on real-world constraints like context windows, concurrency, and latency (reported ~40% latency reduction and <2s average response). Experienced orchestrating AI pipelines with Celery and fault-tolerant long-running workflows with Temporal, and has applied NLP model tradeoff testing (Word2Vec vs BERT) to drive measurable accuracy gains.”

“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.”

“Python backend engineer (BetterWorld Technology) who owns microservice systems end-to-end on Azure, including Kubernetes deployments, CI/CD, and production monitoring/alerting. Has hands-on experience integrating SQL/NoSQL (including Cosmos DB with vector search/graph workflow) and has built a Kafka + Spark Streaming pipeline to Snowflake with a reported 40% latency reduction.”

“DevOps engineer (State Farm) with hands-on ownership of Python backend services and data pipelines, deploying microservices and workers on Kubernetes using GitOps (Argo CD). Has led complex cloud-to-on-prem/hybrid migrations with staged cutovers and rollback planning, and built Kafka-based real-time streaming pipelines with schema governance, autoscaling, and strong observability.”

“Applied AI/ML engineer with hands-on production experience building a RAG-based AI assistant for pharmaceutical maintenance troubleshooting using LangChain + FAISS/Pinecone, including a custom normalization layer to handle inconsistent terminology and duplicate document revisions. Also built Airflow-orchestrated pipelines for document ingestion/embeddings and predictive maintenance workflows (SCADA ETL, drift-based retraining), and partnered closely with production supervisors/quality engineers via Power BI dashboards and real-time alerts.”

“Cross-functional operator/chief-of-staff style leader who took a product from prototype to a live pilot in 3 months, spanning public-sector data normalization, an ML matching engine, a secure API, and KPI/investor demo instrumentation. Strong focus on executive alignment and productivity via Notion-based operating systems plus automated reporting (Python/Power BI), with experience supporting fundraising and go-to-market narratives.”

“Backend engineer who built a Node.js + SQL service integrating with the Google Ads API to periodically upload online and offline conversions via Azure Logic Apps, persisting upload records for ROI reporting. Implemented PII hashing, token validation, redundancy, and detailed failure/status logging for reliability and debuggability. Currently scoping an LLM/agent workflow (likely LangChain) to let marketing bulk-update e-commerce product data using SEO keywords without developer involvement.”

“Game design capstone project owner who built and tuned a full steal/sell/upgrade progression economy for a house-robbery game, including item weight/value balancing, upgrade pacing, and difficulty gates (police/NPC detection). Iterated via playtests and basic telemetry signals (purchase rates, item selection) and implemented a code-driven item attribute system to speed tuning, while also negotiating scope tradeoffs with the team around adding minigames.”

Bhoomika Gururaja

Screened

Intern Product & Project Management professional specializing in analytics-driven delivery

Seattle, WA1y exp

“Product Management Intern who owned an end-to-end sourcing-style initiative for a new digital product launch, coordinating internal stakeholders and external vendors. Uses data-driven, value-focused negotiations and milestone-based delivery management (Jira/Smartsheet) to control scope, timelines, and supplier performance while proactively mitigating cost and schedule risks.”

Moore Macauley

Screened

Intern Backend Developer specializing in AI, multi-agent systems, and computer vision

0y exp

“Backend-focused Python engineer who built core systems for an AI beauty-advice product: converting facial-recognition landmarks into usable facial measurements and dynamically shaping chatbot context for personalized guidance. Also worked on high-volume data ingestion at AINVESTgroup, improving agent context selection via a RAG database when upstream tags were unreliable, and has strong Git/GitOps + automated testing practices from rapid-deadline delivery environments.”

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%).”

Sangat Shah

Screened

Mid-Level Full-Stack Engineer specializing in AWS serverless and React/Node.js

Los Angeles, CA5y exp

“Backend engineer who built and evolved a serverless AWS platform for large-scale live screening events with real-time chat/feedback and streaming (API Gateway/Lambda/DynamoDB/WebSockets/IVS, IaC via Pulumi). Led production refactors and phased migrations using feature flags and dual-write strategies, and has hands-on experience implementing JWT auth, RBAC, and database-enforced row-level security for multi-tenant systems.”