Vetted Jira Professionals

“Solo developer who shipped an Android game (Master Caster) built around touch gesture recognition (P$ algorithm) and data-driven potion/ingredient systems using JSON/dictionaries. Has hands-on experience optimizing Unity projects for mobile constraints (framerate, heat/battery) using techniques directly applicable to VR, and is actively porting the game to VR in Unreal with a focus on accessibility and room/standing/seated play modes.”

“Frontend engineer on Ford EV infotainment HMIs building React + TypeScript workflows for Apple CarPlay/Android Auto device projection and high-stakes reset flows. Deep experience integrating a React HMI with legacy Qt expectations and C++ services via MQTT, using Redux Saga/state-machine patterns to manage complex async device and system operations with strong QA and performance optimization practices.”

“Built and deployed a GPT-4-powered medical assistant for clinical staff to reduce time spent searching guidelines and EHR information, with a strong emphasis on safety and compliance. Uses strict RAG, confidence thresholds, and fallback behaviors to prevent hallucinations, and runs production-grade workflows orchestrated with LangChain/LangGraph plus Docker/Kubernetes/MLflow and monitoring for reliability and cost.”

“Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.”

“Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.”

“Software engineer with startup and capstone experience who improved an ~8-hour database refresh workflow by moving API calls to asynchronous execution and then addressing API rate limits via throttling. Emphasizes performance profiling/logging, strong developer onboarding documentation practices, and disciplined Agile/Jira bug triage and expectation-setting with stakeholders.”

“Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).”

“LLM/agentic workflow specialist with healthcare deployment experience who has taken LLM-based automation from prototype to production using operator-in-the-loop validation, RAG-style retrieval, RBAC, and monitoring for sensitive data compliance. Demonstrated real-time incident resolution (retrieval timeouts due to network/proxy misconfig) and strong GTM support—hands-on developer workshops and sales demos translating technical safeguards and real-time ETL into measurable ROI (70% ops reduction, ~$200K/year savings).”

“Built and shipped multiple production LLM/agentic systems, including an agentic RAG NL-to-SQL analytics app that cut manual reporting from 9 hours/week to 15 minutes by grounding on schema-aware retrieval and robust fallback/monitoring. Also implemented a LangChain supervisor-orchestrated enterprise IT automation agent that routes requests for search, identity validation, and action execution, and created a RAG search tool spanning Jira/Confluence/SharePoint for operations stakeholders.”

“Backend engineer with Walmart experience owning Python data-processing/integration services alongside ASP.NET Core. Has deployed containerized services to Kubernetes via OpenShift with Jenkins CI/CD and GitOps-style config management, and has led phased migrations modernizing VB6/classic ASP apps to ASP.NET Core on OpenShift/Azure. Also implemented Kafka-based real-time pipelines with a focus on reliability, idempotency, and observability.”

“Backend/platform engineer (American Express) who built a Flask-based orchestration layer to automate infrastructure provisioning and integrated Azure AD/JWT RBAC security. Strong in PostgreSQL/SQLAlchemy performance optimization (70%+ query-time reduction) and scalable async/event-driven architectures, including ML inference pipelines (SageMaker/Azure ML/Hugging Face) and high-throughput job queues (Celery/Redis) with reliability patterns like DLQs and idempotency.”

“Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.”

“Healthcare-focused applied ML/LLM engineer who has deployed production systems including an LLM medical documentation assistant that summarizes unstructured EHR notes into physician-ready structured outputs. Experienced building secure, compliant pipelines (PHI minimization, RBAC, encryption) and scaling via Docker/Kubernetes/Azure ML, plus orchestrating ETL/ML workflows with Airflow and Kubeflow; also built an LLM-driven clinical coding assistant at Centene with measurable performance metrics.”

“Built and deployed a production RAG-based document Q&A system on Azure OpenAI to help business teams search thousands of PDFs/Word files, using Qdrant vector search, MongoDB, and a Flask API. Demonstrates strong production engineering (streaming large-file ingestion, parallel preprocessing, monitoring/retries) plus systematic prompt/embedding/chunking experimentation to improve accuracy and reduce hallucinations, and has hands-on orchestration experience with ADF/Airflow/Databricks/Synapse.”

“Backend engineer who led major modernization efforts at GoDaddy, migrating legacy Perl services to Python/FastAPI with an incremental rollout strategy, containerization (Docker/Kubernetes), and CI/CD (Jenkins/GitHub Actions). Strong focus on secure, reliable API design (JWT, RBAC, PostgreSQL row-level security), rigorous testing, and data integrity—plus experience hardening an automated web-scraping pipeline against changing site structures and downtime.”

“Sourcing/procurement professional from Pavana Impex who has owned end-to-end sourcing for production-critical materials, combining spend/demand analytics with hands-on supplier onboarding, negotiation, and production-to-delivery execution. Demonstrates strong trade and landed-cost acumen (HS classification/COO, broker coordination, packaging changes) and a structured approach to supplier performance improvement using scorecards, CAPA, and OTIF/OTD tracking.”

“Applied NLP/ML in healthcare and financial services, including fine-tuning BERT on unstructured EHR text and building embedding-based similarity search for clinical concepts. Also redesigned a Wells Fargo fraud detection data pipeline using modular Python + AWS Glue/Step Functions, cutting runtime ~40% with improved monitoring and reliability.”

“Backend engineer on Morgan Stanley’s trade risk and compliance platform, building Java/Spring Boot microservices that validate equity and fixed-income trades at multi-million-events/day scale. Shipped an LLM-assisted trade exception analysis feature using RAG over internal policy documents and trade history, with production-grade guardrails (confidence thresholds, audit logs, human-in-the-loop) and measurable performance wins (~30–35% faster reporting) through PostgreSQL tuning and Redis caching.”

“Enterprise CSM/program lead specializing in AI-powered search and workflow automation, who owned an end-to-end generative AI chatbot rollout that replaced manual Excel-based RFP processes and achieved 4.5/5 CSAT. Leveraged outcomes to expand the account into two additional use cases (tripling ARR) and has a track record of influencing product priorities (UI personalization) and driving Voice AI expansions tied to operational support workflows.”

“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.”

“QA automation engineer who built and maintained a Selenium WebDriver + Java hybrid framework (data/keyword-driven) using POM, TestNG, and Maven, and integrated it into CI with PR gating and nightly regression. Strong focus on stabilizing flaky tests (wait strategies, locator robustness, test data control) and caught a critical UI/backend mismatch that could have caused duplicate money transfers before release.”

“Customer Success/implementation leader with enterprise experience at ADP managing payroll tax compliance for major brands (e.g., McDonalds, Staples, Williams Sonoma) and coordinating closely with product/compliance/engineering to reduce errors and escalations. Also led cross-functional operational rollouts at Starbucks, improving customer satisfaction by 27%, and currently at Together Groups influencing product roadmap via therapist/participant feedback to lift onboarding engagement by 40%.”

“Backend-leaning full-stack engineer with production experience in both healthcare (claims enrichment/interoperability at Abacus) and finance (Goldman Sachs pricing/risk APIs + React dashboards). Built an event-driven AI grading platform using Postgres Debezium CDC + Kafka + FastAPI on AWS that cut manual grading ~70% and served 1000+ students, with strong emphasis on reliability, testing, and performance tuning.”

“UE5 C++ gameplay programmer who has built core gameplay frameworks (characters, AI, abilities, inventory/interaction, dialogue, weapons, save) and shipped on Steam (Zone 13). Demonstrated strong profiling and optimization skills by using Unreal Insights to diagnose CPU frametime spikes and removing visible hitching with a custom C++ object manager, plus experience with replicated systems using GAS and Fast Array Serialization.”