Vetted Jira Professionals

Wafi Hassan

Screened

Intern Software Tester specializing in SQA automation and backend API validation

Remote1y exp

“Software engineer with medical-domain experience at Philips focused on end-to-end systems integration and reliability, including integrating C# xUnit automated test suites with backend services and CI-driven staging deployments. Also built a Python/scikit-learn typing speed analyzer integrating data collection, model training, and a real-time user interface; interested in transferring this systems/debugging rigor into robotics despite no ROS/robotics project experience yet.”

PAVEL A ASPIAZU

Screened

Senior Paid Media (SEM/PPC) Manager specializing in Google Ads and Meta performance marketing

McLean, VA26y exp

“Paid media performance marketer with agency experience owning a high-spend account for ArcPoint Labs, running multi-channel Google Ads (search/display) and Meta campaigns to drive medical testing appointments and sales. Reported lifting ROAS from ~2x to ~6–7x within ~18 months while supporting expansion from 30 to 60 U.S. locations, using disciplined attribution, constant A/B testing, and structured campaign health audits.”

Sanjana Akula

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY5y exp

“Front-end engineer with experience at Optum and Wells Fargo maintaining internal React/Angular component libraries and design-system-aligned UI modules used across multiple apps. Known for stabilizing shared libraries via semantic versioning, Jest test automation, and high-quality documentation, plus measurable performance wins (≈40% faster dashboard loads) through profiling-driven React and API optimizations.”

Snehitha Penumaka

Screened

Mid-level AI/ML Engineer specializing in predictive modeling and cloud ML pipelines

Dallas, TX3y exp

“LLM engineer/data engineer who has deployed production RAG systems for internal-document Q&A, building end-to-end ingestion, embedding, vector search, and FastAPI serving while actively reducing hallucinations and latency through rigorous retrieval tuning and caching. Also experienced in orchestrating cloud data pipelines (Airflow, AWS Glue, Azure Data Factory) and partnering with non-technical business teams to deliver AI solutions like automated document review.”

Mo Arab

Screened

Executive Technology Leader specializing in Cloud, Managed Services & AI/LLM integration

Los Angeles, CA25y exp

“Engineering/technology leader with experience at Evocative and through a merger with Hivelocity, aligning tech roadmaps to managed services growth. Led multi-region self-hosted cloud and automation initiatives that cut delivery time from days to hours/minutes and informed cost-saving infrastructure decisions (reported $500K OPEX savings). Known for scaling teams with pod ownership, agile/intake governance, and disciplined rollout practices that protect uptime and security.”

Pravalika Kuppireddy

Screened

Mid-level AI/ML Engineer specializing in Generative AI and intelligent automation

4y exp

“LLM engineer who built and productionized a system to classify GitHub commits (performance vs non-performance) using zero-/few-shot approaches over commit messages and diffs, working at ~5M-record scale on multi-node NVIDIA GPUs. Experienced orchestrating end-to-end LLM pipelines with Airflow and GitHub Actions, and emphasizes reliability via testing, guardrails, and observability while collaborating closely with non-technical product stakeholders.”

“Data analyst with cross-industry experience spanning insurance analytics at L&T Infotech and experimental imaging analytics at Mylyser. Stands out for building scalable SQL/PySpark data pipelines, standardizing business-critical metrics like claims lifecycle and policy retention, and delivering measurable impact such as 50%+ faster query performance and a 15% reduction in claims settlement time.”

“Analytics professional with experience spanning financial services and e-commerce, including NAV reconciliation/reporting at State Street and revenue optimization work on checkout and retention. Stands out for combining strong SQL/Python data engineering with business-facing analytics, delivering measurable gains like 3-5% conversion improvement and 8-10% payment success uplift.”

Anirudh Venkatesh

Screened

Mid-level XR/Unity Developer specializing in AR/VR and immersive applications

Riverside, CA5y exp

“Unity developer with hands-on experience across VR, AR, multiplayer, and AI-driven gameplay systems. They’ve owned end-to-end interaction architecture for VR cognitive testing focused on accessibility, integrated Gemini-based command systems into gameplay, and shipped cross-platform immersive applications spanning Magic Leap 2, iOS, and Photon-powered multiplayer experiences.”

“Built and deployed an end-to-end fintech product, FinSight, for bank statement analysis and financial Q&A using a production-style RAG architecture. Stands out for combining FastAPI, OpenAI embeddings, FAISS, hybrid SQL/vector retrieval, and practical reliability work like chunking optimization, validation, and low-latency performance tuning.”

“Backend-focused engineer with hands-on experience deploying AI-driven document processing and RAG-based workflows using Python, LangChain, FAISS, and REST APIs. Has owned projects from requirements through post-launch monitoring, including debugging production retrieval issues and building reliable pipelines for messy PDFs/scans and compliance-oriented document analysis.”

“UE5 Blueprint-focused gameplay/system designer who shipped an XR interactive experience (“Echoes of the Moon”), owning interaction logic, progression triggers, state management, and animation syncing through ship. Emphasizes modular component-based architecture with interfaces and data-table-driven tuning, plus strong profiling/optimization skills (refactoring Tick-heavy systems to event-driven) validated through 20–30 user playtests and mobile XR (Android) frame-budget constraints.”

“Performance marketing specialist with hands-on ownership of $50K+/month spend on the AdOn Network at RhythmOne, focused on driving new-user growth and on-site engagement. Known for rigorous, variable-isolated testing across keywords, placements, and ad copy, plus clear client reporting tied to engagement and efficiency metrics.”

“Software engineer with robotics and data-platform experience from CVS Health, spanning Java/Spring Boot microservices, secure APIs, React dashboards, and Snowflake/SSIS ETL optimization. Hands-on ROS 2 developer who built real-time LiDAR obstacle-detection nodes, improved SLAM performance, and coordinated multi-robot communication using DDS, with simulation/testing via Gazebo and CI/CD deployments using Docker and Jenkins.”

“Unity/C# developer focused on Meta Quest VR simulations and indie game development; built a factory onboarding VR experience largely solo, including modular scenario orchestration, interaction systems, and branching NPC dialogue. Also created multiple Unity games in the last year and built reusable internal packages (game management + UI/screens), while using an AI-driven pipeline for rapid prototyping and 3D asset generation.”

“Unity gameplay engineer with experience across multiple genres (city builders, match-3, RTS) including implementing an open-world isometric fog-of-war system optimized via chunking and multithreading. Has shipped multiplayer features using Photon/UNet and has dealt with real-time synchronization/ownership conflicts, and also applies AI automation to speed up code reviews and improve Jira/merge request workflows.”

“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”

“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”

“Backend engineer who owned an order management API built with Python/FastAPI and PostgreSQL, integrating payment and shipping providers with strong reliability patterns (idempotency, async workers, retries/backoff, circuit breakers). Experienced deploying services to Kubernetes using a GitOps model with ArgoCD (auto-sync, self-healing, pruning, rollbacks) and building high-volume Kafka streaming pipelines. Has also supported phased cloud-to-on-prem migrations with a focus on security monitoring/SIEM log continuity.”

“Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.”

“Software engineer with experience at Wipro Technologies and Wells Fargo building React-based SPAs, reusable component libraries, and developer documentation. Demonstrated strong performance engineering (React.memo, list virtualization, code splitting) with reported >50% rendering-time improvement, plus hands-on production support by diagnosing API outages via monitoring/logs and implementing traffic/server fixes. Comfortable leading workstreams in fast-changing environments using Kanban and tight stakeholder feedback loops.”

“ML/MLOps practitioner from Discover Financial who built and deployed a real-time AI fraud detection platform (LSTM + VAE) on AWS SageMaker with Docker/FastAPI and Jenkins-driven CI/CD. Demonstrated measurable impact (30% accuracy lift, 25% fewer false alerts) and deep expertise in class-imbalance mitigation, drift monitoring, and orchestration (Airflow/Kubeflow), plus strong stakeholder adoption via Power BI dashboards for fraud/compliance teams.”

“Full-stack developer with strong cloud/on-prem focus (AWS, VPC networking) who has improved production reliability by bringing manually created IAM/security group resources under Terraform and standardizing environments. Demonstrated end-to-end troubleshooting across app + infrastructure + networking (traffic capture revealed proxy response truncation) and delivered Python-based monitoring/reporting enhancements that improved ops visibility and turnaround.”

“Worked on large financial analytics datasets combining complaint text, transaction logs, and demographics; built end-to-end NLP/ML pipelines (TF-IDF + Random Forest) and data integration in BigQuery with Tableau reporting, citing ~95–98% accuracy. Also implemented entity resolution with fuzzy matching and semantic linking using BERT sentence-transformer embeddings stored in FAISS, including fine-tuning on labeled pairs to improve search/linking relevance.”