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Vetted Jira Professionals
Pre-screened and vetted.
Sumit Kothari
Junior AI/Full-Stack Engineer specializing in LLM apps and RAG systems
“AI engineer who built and shipped a production AI document-understanding/search system at Sumeru Inc, including a full RAG + LLMOps evaluation stack (MLflow, DeepEval, RAGAS) deployed on GCP. Also developed LangChain/LangGraph multi-agent workflows for UAV flight-log analysis and has experience presenting AI solutions to non-technical stakeholders and prospect clients to drive POCs.”
Sanket Dumbare
Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms
“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”
Lavanya Aggarwal
Mid-level Product Marketer specializing in GTM strategy for tech and media
“Marketing/paid social creative lead who recently ran a 3-month campaign for the Shortzy! app, owning strategy through QA while coordinating freelancers on a small budget. Combines entertainment/on-set direction experience with performance marketing fundamentals (A/B testing, CPA/ROAS/CTR) from Google Marketing certification work, plus conversion assets like landing pages and subscription messaging.”
Matthew Eis
Mid-level QA Tester specializing in video game testing and localization
“Game QA professional with live production experience at Nexon America owning localization verification for new MapleStory questlines (quests, VO, subtitles) and managing issues through Jira-based regression. Previously identified and documented a hard-to-repro main-quest progression blocker on Horizon Zero Dawn: Forbidden West, providing video-backed repro steps that enabled a fix before the next build shipped.”
Sreelekha Vuppala
Mid-level Data Scientist specializing in Generative AI, MLOps, and cloud data platforms
“GenAI/ML engineer (CitiusTech) who has deployed production RAG systems for compliance/operations document Q&A, using Pinecone + FastAPI microservices on Kubernetes with strong monitoring and guardrails. Also built a GenAI-powered incident triage/routing solution in collaboration with non-technical stakeholders, achieving 35% faster response times and 40% fewer misclassified tickets, and has hands-on orchestration experience with Airflow and AutoSys.”
Prashant Salunke
Mid-Level Software Development Engineer specializing in full-stack and cloud-native systems
“Backend engineer who has shipped production LLM-powered features, including an AI-assisted developer tool on AWS (Spring Boot) and a blog platform capability using embeddings + Elasticsearch for semantic retrieval and LLM-generated summaries/recommendations. Demonstrates practical tradeoff management (quality/latency/cost), guardrails to reduce hallucinations, and evaluation-driven iteration using real user queries and observability via ELK.”
Akriti Agrawal
Senior QA Manager / QA Lead specializing in automation and Agile delivery across Banking and FinTech
“QA leader with end-to-end ownership of a web-UI automated B2B pricing platform at Cargill, known for using defect trend analytics (Jira/Jira AI) to uncover systemic config/integration risks before UAT/production. Implemented durable CAPA controls (config-change impact assessment gates) and improved release transparency with Copilot-generated Confluence readiness dashboards; cites 15% logistics cost reduction and 60% operational efficacy improvement. Also coordinated cross-shore QA teams across multiple countries with structured cadences and escalation paths.”
Sriraj Samala
Mid-level Data Analyst specializing in business analytics and BI
“Analytics professional with higher education experience at the University of Dayton, focused on turning inconsistent operational data into standardized metrics and recurring dashboards. They combine SQL, Python, and Power BI to automate reporting, improve data integrity, and reduce manual reporting by 30%, with outputs adopted in semester planning and cross-department performance tracking.”
Supreet Purthpli
Mid-level AI/ML Software Engineer specializing in cloud-native MLOps and FinTech
“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”
Kashish Jain
Junior Software Engineer specializing in backend systems and full-stack development
“Full-stack developer who uses AI thoughtfully as a productivity multiplier rather than a substitute for engineering judgment. Built a stock search platform with React, Node.js, and MongoDB, and has experimented with multi-agent workflows across frontend, backend, debugging, and documentation while keeping rigorous human review over logic, testing, and maintainability.”
sanketh koritikanti
Mid-level Full-Stack Python Developer specializing in cloud, data engineering, and AI/ML
“Full stack Python developer who actively integrates AI coding assistants into day-to-day engineering work, including code generation, debugging, testing, and documentation. Has also coordinated multi-agent workflows across backend, frontend, testing, and code review, showing an applied, productivity-focused approach to AI-enabled software delivery.”
Vinay Sanagapalli
Mid-level Software Development Engineer specializing in cloud-native FinTech and SaaS systems
“Engineer focused on AI-assisted and multi-agent software development, with hands-on experience designing structured agent workflows for implementation, testing, validation, and architectural review. Stands out for treating AI as an accelerator rather than a replacement, combining practical experimentation with strong attention to engineering fundamentals and operational concerns like observability, latency, and cost.”
Shubham Deshpande
Mid-level Frontend Software Engineer specializing in Angular and React web applications
“Frontend-focused engineer with experience delivering a major licensing-model migration, moving customers from legacy key-based licensing to a dynamic renewal experience. Strongest signals are in React/TypeScript architecture, reusable component design, micro frontends, and frontend quality/performance practices.”
John Patton
Executive Atlassian and Agile transformation leader specializing in AI-enabled enterprise collaboration
“Product leader with hands-on experience modernizing enterprise internal tooling and shipping AI-enabled support workflows. At Peloton, they led the end-to-end migration of Jira, Confluence, and JSM from on-prem Data Center to cloud; at Atlas Vega, they implemented a RAG-based Slack/JSM support assistant with strong governance, data hygiene, and measurable support outcomes.”
Per Jorgensen
Director-level product and UX leader specializing in digital products and enterprise SaaS
“Product and UX leader with experience launching a new direct-to-consumer ecommerce channel inside an enterprise business and later optimizing it to double revenue and conversion. Also built early AI-assisted workflows in regulatory/risk software, with a strong emphasis on trust, human oversight, and adapting quickly to new domains through first-principles product thinking.”
Sanket Mungikar
Mid-level Software Engineer specializing in distributed backend and AI analytics platforms
“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”
Sai Divya Mulukala
Mid-level Full-Stack Software Engineer specializing in FinTech and distributed systems
“Full-stack engineer with experience building operational dashboards at Walmart and improving digital banking experiences at Bank of America. Stands out for tracing performance issues across frontend, APIs, and backend services, including cutting response times from 1.2s to 700ms and resolving duplicate event-processing problems in distributed systems.”
Siya Doshi
Intern Software Engineer specializing in full-stack development and machine learning
“Entry-level software engineer with strong full-stack experience building React/TypeScript and Node.js analytics products, especially around performance optimization for large datasets. Stands out for combining hands-on engineering with user discovery, and for delivering measurable wins like 40% fewer API calls, page load improvements from 3.2s to 1.1s, and 70% faster PostgreSQL queries during an internship at Tapastry.”
Naseer Jackson
Mid-level Full-Stack Engineer specializing in web platforms for retail and FinTech
“Front-end engineer who built a sophisticated browser-based registration platform for the JPMorgan Corporate Challenge, serving global users and handling team-based registration complexity, concurrency, and performance. Stands out for combining React/TypeScript UI engineering with accessibility improvements, UX polish, and production-minded reliability practices like Datadog monitoring and Kubernetes health checks.”
Nithyashree Raghunathan
Mid-level Full-Stack AI Engineer specializing in agentic systems
“QA/data pipeline engineer with hands-on AI product building experience, spanning enterprise AWS migration testing for Belgium postal services and personal multi-agent systems in fintech and recruiting. Stands out for combining rigorous validation and production stability work with modern LLM orchestration, guardrails, and messy-document normalization workflows.”
Murali Marupudi
Mid-level Backend Engineer specializing in Python microservices and scalable cloud systems
“Backend engineer focused on high-throughput Python/Flask systems on AWS, with strong scaling and performance tuning experience (e.g., PostgreSQL join reduced from ~3s to <200ms; background aggregation cut from 10 minutes to <90 seconds with 8x throughput). Has also integrated ML model serving into production APIs (churn prediction) using Celery/Redis batching and AWS Lambda/S3, and designed secure multi-tenant architectures with PostgreSQL schema isolation and row-level security.”
Sai B
Mid-level Python & AI/ML Engineer specializing in backend and LLM systems
“Built an internal AI-powered document search and Q&A platform at BNY that let employees query company documents in natural language and get grounded answers in seconds. Brings practical full-stack and LLM systems experience across React/TypeScript, FastAPI, Pinecone, OpenAI, and Claude, with clear emphasis on retrieval quality, hallucination reduction, and production monitoring.”
Athish Venkatachalam
Mid DevOps Engineer specializing in cloud infrastructure and GitOps
“Platform/DevSecOps engineer who combines full-stack product ownership with practical LLM systems in production. They built a self-service secrets management portal that reduced DevOps bottlenecks while maintaining compliance, and shipped AI-powered deployment debugging and security-remediation workflows with strong guardrails, monitoring, and human-in-the-loop controls.”