Vetted Jenkins Professionals

“QA automation engineer focused on backend/API quality who owned an end-to-end API regression suite and integrated Cypress/JS automation into GitLab CI with smoke-vs-nightly regression gating. Caught a critical auth security regression (expired tokens returning 200 instead of 401) before production and is strong in stabilizing flaky tests using network interception and actionable CI reporting.”

“End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.”

“Backend-focused Python engineer who owned high-traffic internal services end-to-end (FastAPI/Django) including REST/GraphQL APIs, PostgreSQL optimization, async task processing via SQS, and full CI/CD. Strong Kubernetes-on-EKS and GitOps (ArgoCD + Helm) experience, plus Kafka real-time streaming work and phased cloud-to-on-prem migration support.”

Anjana Priya Swathi Samudrala

Screened

Junior Full-Stack AI Developer specializing in LLMs and RAG applications

Orlando, US2y exp

“Product-minded software engineer who owned a Shopify POS app end-to-end at Swym, shipping an MVP and then scaling iteration speed with E2E automation and CI/CD—resulting in a Shopify Badge, Top-5 App Store ranking, and +40% new user acquisition. Also built an ESG insights tool using React/TypeScript + FastAPI with Snowflake and a RAG pipeline, plus microservices patterns (async jobs, queues, DLQs, autoscaling) and internal Metabase/SQL analytics dashboards.”

Isha Harne

Screened

Intern Software Engineer specializing in ML applications and LLM platform engineering

New York, NY1y exp

“Full-stack engineer who builds and scales customer-facing and internal AI products end-to-end (React/TypeScript/FastAPI/MongoDB) with strong product instrumentation and rapid MVP iteration. Built an AI-powered code review assistant adopted across teams and integrated into CI/CD, reducing manual review time by 30%+, and has hands-on experience with LLM retrieval/reasoning systems (LangChain + FAISS) and microservices scaling using RabbitMQ, Docker, and AWS.”

fahliyanto prasetyo

Screened

Mid-level QA Engineer specializing in digital banking mobile and web testing

East Jakarta, Indonesia8y exp

“QA professional with experience spanning mobile/web applications plus API and backend behavior testing, using Jira and TestRail along with exploratory/regression and compliance-focused verification. Describes a structured approach to meeting tight deadlines by breaking work into modules, estimating test execution timelines, and using AI tools to accelerate documentation and analysis when test case volume is high. No direct console testing or TRC/XR/LOT certification experience yet, but has a compliance-testing foundation.”

Jonathan Grebe

Screened

Mid-level Robotics Software Engineer specializing in ROS, C++ and embedded Linux

Ottawa, Canada7y exp

“Robotics software lead at Icor who grew from intern to owning the end-to-end software lifecycle for a mobile manipulator platform deployed to 300+ customers globally. Deep hands-on ROS2/MoveIt2 and navigation-stack integration (URDF/TF, sensors, behavior engine) plus production infrastructure (CI/CD, OTA, field OS upgrades) and real-world performance tuning for motion planning in EOD multi-robot environments.”

Deva Sai Kumar Bheesetti

Screened

Mid-level Full-Stack Engineer specializing in data automation, cloud & AI

Lowell, MA5y exp

“JavaScript engineer who effectively "maintains" an internal open-source-style React/Node.js shared library used by multiple teams—owning API stability, semantic versioning, CI/testing, logging, and documentation. Demonstrates strong cross-team debugging and change-management skills (schema-driven refactors, feature flags, validation layers) to ship new features without breaking existing workflows, plus a profiling/benchmarking-driven approach to performance.”

Jyothi RajaMurugan

Screened

Mid-level .NET Full-Stack Developer specializing in finance and healthcare web apps

New Jersey, USA5y exp

“Full-stack engineer with end-to-end ownership of a data-heavy financial dashboard module at Brown & Brown Insurance, spanning .NET Core APIs, EF/SQL Server, and React/TypeScript UI. Demonstrates strong focus on performance tuning (indexing, pagination, caching, async) and secure service design (Azure Key Vault, JWT/RBAC) in a microservices context.”

Tanisha Pradeep Bhola

Screened

Mid-level Software Development Engineer specializing in backend, cloud, and microservices

Dayton, Ohio4y exp

“Accenture engineer with hands-on experience taking an NLP sentiment analysis system from prototype to production, emphasizing robustness to noisy data, scalability, and observability (dashboards for latency/error/throughput). Also supports customer-facing teams with demos and PoCs, translating client requirements into secure, scalable architectures and troubleshooting LLM/agent workflows via logs and step-level traces.”

LAKSHMI KATTAMURI

Screened

Mid-level Embedded Software Engineer specializing in RTOS and microcontroller firmware

Boston, MA4y exp

“Backend/embedded-focused engineer with hands-on experience designing real-time, memory/power-constrained firmware architectures and also building Python/FastAPI services. Demonstrates strong production rigor across migrations (strangler pattern, shadow reads, feature flags), security (OIDC/JWT, RBAC/ABAC, Postgres RLS), and robustness for async workflows (idempotency, event ordering, state machines).”

Haytham Nasri

Screened

Software Engineering Manager specializing in cloud-native mobility and enterprise Java

Amsterdam, The Netherlands15y exp

“Backend/architecture-focused player-coach who designed and built two partner-facing data APIs using a contract-first (OpenAPI) governance model in Java (Quarkus/Spring Boot). Strong in technical standards, incident response, and delivery systems—improved reliability under peak load (DB/index fix) and sped up delivery by streamlining PR/review processes while maintaining production stability.”

Sai Srujan Vemula

Screened

Mid-level Full-Stack Developer specializing in Java/Spring Boot and React on AWS

CT, USA3y exp

“Full-stack engineer with enterprise experience at Meta System and DXC, owning end-to-end delivery of a shipment visibility portal (React UI in Liferay DXP + Java/Spring Boot REST APIs) with Dockerized deployments and automated test coverage. Has hands-on AWS work across EC2/Lambda/S3 and multiple databases (DynamoDB, RDS, Neptune, DocumentDB), plus built a Python/Flask data migration platform with validation for correctness and repeatability.”

“Senior AI/ML engineer with hands-on experience building production LLM systems in healthcare, including RAG-based clinical question answering and end-to-end MLOps on Vertex AI and Kubernetes. They combine strong platform engineering with applied GenAI work, citing a 35% improvement in factual accuracy and a 30% boost in internal team productivity through modular Python services and CI/CD.”

“ML/AI engineer with strong healthcare insurance domain depth who has owned fraud detection and LLM claims products end-to-end in production. Stands out for combining modern MLOps and RAG architecture with measurable business impact, including millions in fraud savings, 40% faster analysis, and reusable platform tooling that accelerated multiple teams.”

“AI/ML engineer with hands-on experience building a healthcare-focused generative AI application end-to-end, from architecture and data design through deployment, monitoring, and iterative improvement. Particularly strong in multi-agent LLM systems, fine-tuning, and safety guardrails, with measurable impact including a 20% accuracy lift to 91% and 10% latency improvement in a nutrition recommendation pipeline.”

“Healthcare-focused ML/AI engineer who has built clinical note summarization and medical image annotation solutions using LLMs, RAG, and multimodal models. They combine experimentation across major model providers with practical production concerns like monitoring, drift detection, and latency/cost tradeoffs, and also earned 2nd place in a Google hackathon for a medical AI assistant.”

Sai Prudhivi

Screened

Mid Software Engineer specializing in full-stack microservices and cloud platforms

New York, NY4y exp

“Backend-focused engineer with experience building high-volume policy management and enterprise pricing systems, including Django/FastAPI/Flask services, Kafka-based async workflows, and Prometheus/Grafana observability. While they have not yet shipped a customer-facing AI agent or production LLM integration, they bring strong cloud, API, reliability, and scalable system design fundamentals that translate well to responsible AI infrastructure work.”

“Built and launched a production AI knowledge assistant at Virtusa used by 8,000 people, combining RAG, tool use, and strong reliability practices to cut lookup time by 60%. Also owns full-stack delivery, including a real-time transaction monitoring dashboard built with React, Spring Boot, and Kafka handling 200K API requests per day.”

Sri Mounika Jammalamadaka

Screened

Mid-level AI/ML Engineer specializing in GenAI, LLMs, and data platforms

Fairfax, VA6y exp

“Built and helped deploy a production RAG-based LLM assistant for HVAC anomaly diagnostics, partnering closely with field engineers and operations teams to make AI outputs trustworthy in real workflows. Stands out for practical post-launch optimization work—improving retrieval quality, reducing hallucinations, and stabilizing non-deterministic behavior—which contributed to roughly a 40% reduction in diagnosis time.”

“Software engineer currently building for a wealth management platform, with hands-on ownership across React/TypeScript front ends, Azure serverless backends, and SQL data systems. Stands out for turning hackweek concepts into production features, building observability infrastructure from scratch, and delivering measurable gains in latency, uptime, incident response, and client satisfaction.”

“AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.”

“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”

“Backend engineer with deep experience modernizing a provider credentialing/compliance platform with multiple upstream/downstream integrations. Focused on building predictable, scalable REST APIs (primarily ASP.NET Core; framework-agnostic approach applicable to FastAPI), improving performance via DB/query optimization, and hardening workflows with idempotency, transactions, feature flags, and strong auth/RBAC patterns.”