.png){kind=logo}
Vetted MySQL Professionals
Pre-screened and vetted.
Sanskruti Raut
Mid-level AI/ML & Full-Stack Engineer specializing in LLM agents and medical RAG systems
“Full-stack engineer at an early-stage startup building an agentic AI application for enterprise systems, combining customer-facing Next.js/React UI work (30% faster load times) with backend/workflow orchestration using FastAPI + n8n, Redis, and RabbitMQ. Previously at Deloitte USI, built BDD Selenium/Java automation and managed 200+ defects end-to-end using JIRA/JAMA to support on-time production releases.”
Vansh Amara
Junior Software Engineer specializing in AI systems and robotics infrastructure
“Robotics software engineer with hands-on ROS 2 experience building real-time perception/control infrastructure and multi-sensor fusion (radar/ultrasonic + GNSS/IMU) with deterministic latency and safety fallbacks. Debugged rover navigation drift via rosbag replay and timing analysis, improving state estimation by gating GNSS and switching to SLAM when GPS degraded. Also brings strong distributed-systems and build/CI tooling experience (gRPC/Protobuf, Docker, Bazel cross-compilation for ARM/RISC-V, GitHub Actions).”
Rong Hu
Junior Robotics Data Engineer specializing in multi-sensor perception datasets
“Robotics software engineer focused on perception data pipelines and multi-robot coordination. Built ROS 2 (rclpy) nodes for synchronized RGB/ToF/pose processing and scaled a perception training data generation pipeline from single-object to multi-object while preserving backward compatibility. Also has strong DevOps experience deploying containerized APIs on Kubernetes with Kustomize and automated releases via GitHub Actions.”
Jorge Mendoza
Senior Full-Stack Developer specializing in Python, AWS serverless, and data workflows
“Backend/data engineer from ALDI Tech Hub who modernized legacy analytics (Excel/SAS) into production-grade Python services on AWS serverless (FastAPI on Lambda behind API Gateway with Step Functions). Strong in reliability and operations (Cognito auth, retries/timeouts, structured logging, CloudWatch alarms) and data pipelines (Glue ETL with schema evolution); delivered measurable SQL tuning gains (30s to 2s, 70% CPU reduction).”
Sanjana Kirthi
Junior Software Engineer specializing in backend platforms and cloud-native systems
“Backend engineer from Emphasis who modernized legacy, tightly coupled workflow systems into observable, event-driven microservices using Kafka. Led a monolith-to-microservices refactor with shadow traffic, feature flags, canary rollout, dual writes, and reconciliation, and strengthened reliability with idempotent consumers, DLQ/replay, and an outbox pattern to prevent DB/event inconsistency. Strong focus on secure multi-tenant APIs (OIDC/JWT, RBAC/ABAC, Supabase-style RLS) and frontend enablement via OpenAPI and typed client generation.”
Rushwant K
Mid-Level Full-Stack Software Engineer specializing in FinTech and microservices
“Backend engineer with experience at Discover, Dell, and Carpus building high-concurrency microservices and secure APIs. Delivered measurable impact in fintech workflows by integrating credit bureaus (TransUnion/Experian), cutting loan processing from days to minutes and reducing latency 65% through PostgreSQL tuning and caching. Strong in production security patterns (JWT/RBAC, Postgres row-level security for multi-tenant isolation) and low-risk migrations (shadow mode + incremental rollout).”
Smriti Rai
Mid-Level Software Engineer specializing in backend APIs and distributed systems
“JavaScript engineer with Walmart experience contributing to the Yup validation library—reproduced a nested-object validation bug, fixed merge logic, and added test coverage. Strong in systematic debugging/performance isolation (DevTools + timing logs), plus end-to-end ownership including documentation, monitoring, and issue triage.”
Laasya Muktevi
Intern Machine Learning Engineer specializing in forecasting, NLP, and RAG systems
“Intern who built and deployed a production LLM-powered contract analysis system for finance teams: Azure Document Intelligence for text/table extraction plus Gemini prompting to surface key terms and risks via an async API and simple UI. Emphasizes reliability in production with fallbacks, guardrails against hallucinations, and operational concerns like latency/cost/versioning, delivering summaries in under 30 seconds instead of hours.”
sarah robert
Staff RPA & Automation Engineer specializing in Financial Services
“Blue Prism RPA developer in a small FinTech-aligned team who owned ~20 production bots and drove both delivery and reliability. Built a shared VDI/locking design that cut infrastructure cost ~20–30% and routinely handled ServiceNow-driven production incidents end-to-end, including hotfixes and longer-term SDLC fixes. Also acted as a player-coach, training junior hires and maintaining high bot success rates (up to 99% within SLA).”
Surya Mahesh
Mid-level Software Engineer specializing in backend and real-time automotive systems
“Hands-on ML practitioner who built and deployed an end-to-end phishing email classifier (CLI + simple web app), achieving 98% accuracy and reducing manual security triage. Emphasizes production reliability through input validation, graceful failure modes, monitoring/logging, and iterative error analysis, with experience hardening pipelines against messy backend/database data using fallbacks and idempotent processing.”
Atharv Sankpal
Mid-level Data Analyst specializing in financial and healthcare analytics
“Analytics professional with experience at JPMorgan and Deloitte, focused on financial and risk data. They stand out for building scalable SQL/Python data pipelines, KPI and forecasting dashboards, and retention/cohort metrics that improved reporting reliability, forecast accuracy, and planning speed.”
Madhu Ramakrishnappa
Mid-level AI/ML Engineer specializing in LLMs, RAG, and time-series forecasting
“ML/AI engineer with hands-on ownership of production recommendation and RAG systems at Northern Trust. They combine transformer modeling, latency optimization, cloud deployment, and monitoring with measurable business impact, including 14% accuracy gains, 12% engagement improvement, and 19% better query relevance.”
Rakesh Eleti
Mid-level AI/ML Engineer specializing in LLMs, RAG, and healthcare ML systems
“Healthcare ML/AI engineer at Cigna who has owned a clinical RAG pipeline from prototype through production, monitoring, compliance, and iteration. Stands out for combining LLM product delivery with healthcare-grade safety and explainability, driving a 38% retrieval precision gain, 42% hallucination reduction, and meaningful improvements in team velocity and system reliability.”
Praveen LAKSHMAN
Mid-level Software Engineer specializing in backend systems and workflow automation
“Early-career AI engineer currently pursuing a Master's, with hands-on experience building and improving RAG pipelines using LangChain. They stand out for moving beyond naive retrieval into multi-step retrieval and feedback-loop designs to reduce hallucinations, and are now exploring multi-agent systems with distinct retrieval, coding, and validation roles.”
Aravind Sajeev
Senior Full-Stack Software Engineer specializing in scalable enterprise applications
“Full-stack engineer who described building Matrix, a meeting-room booking system across React, ASP.NET Core, and SQL Server. Stands out for owning the workflow end-to-end, emphasizing backend-enforced booking conflict validation, React performance optimization, and integrations like Google Calendar and email notifications.”
Niranjaan Munuswamy
Mid-level Full-Stack Software Engineer specializing in cloud and data engineering
“Backend engineer with experience at Cigna evolving REST API services backed by PostgreSQL, emphasizing reliability/correctness, scalability, and observability. Has hands-on production experience with FastAPI (contract-first design, Pydantic schemas), performance tuning (indexes, caching), and secure auth patterns (OAuth/JWT, RBAC, row-level security via Supabase), plus low-risk incremental rollouts using feature flags and dual writes.”
Abhishek Arugonda
Mid-level Backend Software Engineer specializing in cloud-native microservices
“Backend/platform engineer with experience across Cigna, Cognizant, and a university environment, focused on reliability, distributed systems, and regulated-domain workflows. Stands out for combining Kubernetes/Kafka/AWS infrastructure expertise with a production RAG-based healthcare compliance assistant that cut manual reporting work from 30-45 minutes to under 2 minutes while maintaining strong uptime and data-quality controls.”
“Engineer with a thoughtful, hands-on approach to AI-assisted software development, treating AI as a force multiplier for debugging, prototyping, and large-codebase work rather than a substitute for judgment. Particularly strong in multi-agent coding workflows, contract-driven development, and maintaining consistency across backend, frontend, and testing through shared schemas and OpenAPI-based coordination.”
Aniket Dhanawade
Mid-level Full-Stack Engineer specializing in cloud-native and AI-powered applications
“Candidate has a thoughtful, hands-on approach to AI-assisted software development, treating AI as a pair programmer while retaining ownership of architecture, tradeoffs, and final code quality. They have practical experience using multi-agent workflows to ship small features end-to-end, including planning, execution, and gap detection under human oversight.”
Ankit Yadav
Mid-level Software Engineer specializing in cloud-native microservices
“Backend engineer who shipped a Spring Boot transactions/points feature while using AI selectively for boilerplate and test ideas, keeping core system design decisions in human hands. Stands out for rigorous validation of AI output against database behavior, concurrency, idempotency, and failure scenarios, and has also built a lightweight planner -> code gen -> validator agent-style pipeline with step-level logging and retries.”
Shivam Soni
Mid-Level Full-Stack Software Developer specializing in cloud-native microservices and AI/ML
“Backend engineer who optimized an AI-driven portfolio analytics/insights platform at Fidelity, addressing latency and traffic growth by moving services toward microservices, improving service communication, and tuning API/DB performance. Experienced scaling Python/FastAPI services with Docker + Kubernetes autoscaling, and strengthening security/privacy for sensitive client portfolio data used in LLM-based reporting.”
Jafeeza Shaik
Mid-Level Software Engineer specializing in cloud-native microservices and data platforms
“Robotics software engineer focused on multi-robot fleet orchestration in ROS 2, owning the fleet manager and task dispatch layer for pick/drop workflows. Strong in real-world reliability and safety (heartbeats, idempotent tasking, E-stop/localization confidence gates) and in debugging timing/state issues via telemetry alignment and rosbag replay, with experience in simulation, CI/CD, Docker, and Kubernetes-based deployments.”
Aditya Rouniyar
Intern Full-Stack Software Engineer specializing in cloud, voice AI, and billing systems
“Product-minded full-stack engineer at a B2B startup who ships high-stakes customer-facing features fast: delivered a Spanish AI support agent in 2 weeks by benchmarking LLMs and using native Spanish system prompts, reaching 90% resolution. Built the company’s first monetization system (hybrid subscription + usage) with Stripe/Firebase, emphasizing secure JWT-based flows and idempotent webhooks, and led a microservices decoupling effort that cut developer onboarding time by 50%.”