Vetted Jira Professionals

“Built and deployed a GenAI-powered PhD career intelligence platform at NYU that maps academic backgrounds to career paths and converts long academic CVs into job-ready resumes. Stands out for treating LLM systems as structured production pipelines—combining NLP extraction, embeddings, orchestration, and AWS deployment—to improve recommendation quality and cut resume preparation time by 70%.”

Dhriti Kanchan

Screened

Mid-level Data Analyst specializing in healthcare and financial analytics

Texas, USA5y exp

“Analytics-focused candidate with hands-on experience turning messy CRM, e-commerce, payments, and support data into trusted reporting datasets using SQL and Python. They have owned end-to-end churn and retention analytics work, including RFM-based segmentation, dashboard delivery, and metric standardization across sales, marketing, and finance.”

Eugene Nelepko

Screened

Executive growth leader specializing in AI-powered SaaS, marketplaces, and e-commerce

San Francisco, CA13y exp

“Growth leader with strong zero-to-one and systems-building experience across e-commerce and retail media. Most notably, they proposed and launched a new retail media division from scratch, presold demand before product build, and scaled it to $1.5M ARR with 85% margin, while also building data-driven lifecycle and acquisition systems that materially improved activation and CAC efficiency.”

“Product/UX designer with hands-on front-end implementation experience who has worked across both consumer and enterprise contexts, including a veterinary hospital funnel redesign and an AML fraud detection system. Stands out for tying UX decisions to measurable business outcomes, including a 17% reduction in dropoff after redesigning package selection and validating changes through usability testing.”

“AI and platform engineer with 5 years of experience who built a production knowledge assistant for Verizon end-to-end, from architecture through deployment, monitoring, and incident hardening. Stands out for combining modern LLM/RAG systems with enterprise-grade rigor, including validation layers, observability, versioning safeguards, and measurable impact on technician productivity and retrieval quality.”

“Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.”

“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.”

Sai Sri Kolanu

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and production ML systems

Dearborn, MI4y exp

“Built and shipped an AI-powered RAG diagnostic assistant at Ford for EV technicians, integrating GPT-based models with LangChain, FAISS, and SageMaker into real technician workflows. Stands out for combining strong production LLM architecture with practical safety guardrails, monitoring, and measurable impact: 45% better diagnostic accuracy and roughly 30 minutes saved per case.”

“AI/full-stack engineer in gaming analytics who joined Omnic.ai at a 2-person stage, helped grow with the company, and built both backend and frontend for real-time gameplay analysis products. He combines computer vision production experience with LLM/RAG systems work, and has already led 4 employees while shipping 12 models in a fast-moving startup environment.”

“PMP-certified project/program manager with 13 years of experience leading high-stakes federal intelligence and law enforcement technology programs. Has owned a $15M+ portfolio spanning AI/ML analytics platforms, AWS/Azure cloud initiatives, and enterprise data integrations, with active Secret Clearance and a track record of improving executive visibility and reducing escalations in compliance-heavy environments.”

Namrata Shivshankar patil

Screened

Mid-level Backend/Full-Stack Engineer specializing in cloud, AI, and distributed systems

Arlington, TX6y exp

“Built and shipped internal AI support systems spanning Angular/TypeScript frontends, Java/Spring/AWS backends, and Claude-powered troubleshooting workflows. Stands out for combining full-stack product delivery with practical LLM engineering, including RAG, structured outputs, production evals, and careful human-in-the-loop safety decisions. Has shipped systems serving 150-800 daily sessions at 99.5% availability while reducing repetitive support burden.”

“PMP-certified implementation project manager with 7+ years leading enterprise SaaS rollouts in government-funded healthcare and human services environments. At Caseworthy, they have owned full-lifecycle deployments of ClientTrack and the Azure OpenAI-based CARA AI copilot, managing complex data migration, compliance, and stakeholder governance challenges across multiple concurrent projects.”

“Backend-leaning full-stack engineer who has shipped real-time, customer-facing dashboards and ticketing/payment features at Freshworks and Global Payments. Strong in Python API design (Django/Flask/FastAPI) and React/TypeScript UIs, with hands-on experience scaling PostgreSQL for high transaction volumes and operating services on AWS, including incident response and HIPAA-aligned security controls.”

Saumay Killa

Screened

Mid-level Full-Stack Engineer specializing in AI SaaS and web applications

New York, NY3y exp

“Built a career platform feature end-to-end that generates tailored resumes and cover letters using a React/TypeScript frontend, Postgres, and AWS Lambda/SQS backend. Strong in event-driven, serverless architecture and pragmatic product iteration, with a quantified 60% improvement in onboarding completion after redesigning the UX with resume parsing and a multi-step flow.”

“Frontend-focused engineer with experience spanning AI interview coaching and institutional financial dashboards. Stands out for combining user-centered UI design with deep browser-performance work, including reducing dashboard lag via virtualization and building low-stress, progressive-disclosure interfaces for anxious job seekers.”

“Financial-services software engineer with experience building both full-stack advisor tools and production AI features at Charles Schwab. They owned an automated portfolio rebalancing workflow and helped launch an LLM-powered reporting assistant that cut report-writing time by 70%, while maintaining compliance through strict tool use, evals, and mandatory human review.”

“Backend-leaning full-stack engineer with 7 years of Python experience who has worked on data-heavy products in both healthcare and social media intelligence. Particularly notable for driving Elasticsearch-based search improvements on a B2B social media analytics platform and for building secure healthcare APIs using Flask/Django with OAuth, JWT, and multiple databases.”

“Entrepreneur building an applied-AI tool for geological resource exploration (critical minerals, oil & gas) that overlays proprietary and public data from reports/logs/maps to generate evidence-based greenfield profiling insights. Has spent ~2 years on industry research, built a POC, validated demand with purchasing signals, and developed partnerships/network including USGS, DARPA, and ESRI.”

“Robotics software developer with hands-on ROS experience building a timer-driven closed-loop controller for a differential-drive robot in Gazebo, including square/figure-8 trajectory planning and RViz/rqt_graph-based debugging. Currently extending the system with LiDAR-based obstacle detection, safety overrides, and reactive velocity arbitration for collision-free motion.”

“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”

“At KPMG, built and productionized a secure RAG-based LLM assistant that lets business and risk stakeholders query data warehouses in natural language, reducing dependence on data engineers for ad-hoc analysis. Demonstrates strong production rigor (Airflow orchestration, CI/CD, containerization), retrieval/embedding tuning (rechunking, semantic abstraction for structured data), and reliability controls (confidence thresholds, refusal behavior, monitoring and canary evals).”

“Unity game developer who built a "constraint-driven match resolution" card-game system that encouraged players to think 1–2 moves ahead while keeping interactions as simple as UNO-style matching; reported longer player sessions and positive feedback. Has used Photon to implement most online features in games and leverages AI tools for code writing to boost productivity.”

“Open-source JavaScript contributor focused on performance and maintainability in data visualization libraries—refactored legacy ES5 into modular ES6, added tests/docs, and delivered ~30% faster load times with positive community adoption. Also optimized a React dashboard (~40% load-time reduction) and took ownership in an ambiguous AI product initiative by setting milestones, standing up an initial ML pipeline, and shipping a prototype in ~6 weeks that became the basis for production.”

“Full-stack engineer with experience at Vanguard, PNC, and Humana building customer-facing investment/banking flows and internal ops tools using Angular/React/TypeScript with Spring Boot microservices. Strong in shipping time-sensitive changes safely via automated testing/CI (JUnit/Mockito, Jenkins, SonarQube) and in operating event-driven microservices with Kafka (idempotency, retries, correlation IDs). Improved internal tool adoption by responding to ops/support feedback with query optimization and clearer search results.”