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Vetted SQL Professionals
Pre-screened and vetted.
Asanbai Suranov
Senior QA Engineer specializing in test automation and API/E2E testing
“QA automation engineer with 7+ years across finance/healthcare/utility/services, specializing in Selenium + Cucumber and building automation frameworks. Has tested machine-learning-powered claims prediction features and uncovered complex timing/concurrency failures in subscription payments by simulating delayed webhooks and parallel execution, then driving production fixes end-to-end using disciplined Jira workflows.”
Michael Feola
Senior Full-Stack Engineer specializing in enterprise CMS modernization and accessibility
“CMS-focused developer who has built internal dashboard widgets to migrate and publish client website data when standard tooling fell short, with strong attention to data integrity and rollback. Proactively pushed a hardcoded client homepage toward an admin-configurable widget by creating wireframes and advocating for maintainability. Uses LLM tools to speed up personal automation projects, including Blender-based SVG-to-3D batch processing.”
Arju Singh
Mid-level Machine Learning Engineer specializing in LLM apps, RAG pipelines, and MLOps
“Software engineer with connected-car/automotive production experience who owned an end-to-end remote door lock/unlock feature and introduced unit testing (GTest) plus rig/simulator validation. Also built and productionized an AI-native AWS cloud cost assistant (Lex + GPT-based LLM + Lambda + RAG/vector DB) with guardrails and achieved 94% evaluation accuracy. Helped replace a third-party solution with an in-house build, saving the company ~€9M.”
Mounika Armoor
Senior Full-Stack .NET Developer specializing in Angular/React and cloud (Azure/AWS)
“Gameplay engineer with hands-on ownership of real-time C++/UE5 systems, including an end-to-end ability system and a networked dash feature using client prediction and server reconciliation. Strong in performance profiling/optimization (object pooling, collision-check gating) and applied math for projectile motion validated via debug visualization and QA/playtesting; particularly interested in soccer/football gameplay mechanics and feel.”
Shreyansh Bhalani
Mid-level Full-Stack & ML Engineer specializing in AI SaaS, MLOps, and cloud infrastructure
“Built and shipped an AI-powered driver ranking/assignment system at AffirmoAI using LLM intent classification + RAG over pgvector/Postgres, served via FastAPI with a React UI that explains scores. Drove measurable improvements through optimization and iteration (latency down to <800ms, adoption 60%→90%+) and implemented rigorous eval loops with dispatcher ground truth plus cold-start handling for new drivers.”
Richard Faulise
Director of Engineering specializing in AI-enabled SaaS and mobile platforms
“AI startup co-founder and CTO who helped raise $2.6M in seed funding at RedRex and drove product strategy from ideation through execution. Experienced with rapid experimentation and AI-driven prototyping to validate ideas quickly, and has direct exposure to the VC/accelerator ecosystem (Gener8tor) with a market-first approach to building and pitching startups.”
Kuldip Kuldip
Mid-level Software Engineer specializing in AI automation and distributed systems
“Built and shipped a production LLM-powered email automation agent for procurement that ingests emails/attachments, classifies requests via rules+embeddings+LLM fallback, enriches responses with SAP inventory data, and generates templated replies. Architected it as an event-driven, idempotent Azure Functions/Queues pipeline with schema-constrained outputs, confidence gating, retries/circuit breakers, and Application Insights monitoring—cutting turnaround time from 4–7 days to near real-time while maintaining zero downtime.”
Sai Nikhitha Chowdary Manne
Junior Software Developer specializing in AI/LLM agent systems
“Built an LLM-powered agent within the Nora AI analytics platform to automate e-commerce product performance analysis and generate actionable recommendations (pricing/inventory), designed with production-grade reliability patterns and observability. Emphasizes predictable, schema-validated tool/function-calling pipelines with robust fallbacks, idempotency, and guardrails for messy operational data.”
Yashi Agarwal
Mid-level Machine Learning Engineer specializing in NLP, Generative AI, and RAG systems
“Built and deployed a production LLM-powered phone assistant for a healthcare clinic, combining streaming STT/TTS with RAG over approved clinic documents and strict safety guardrails to prevent unverified medical advice, plus seamless human handoff. Also has hands-on Apache Airflow experience building robust daily ML/data pipelines with data validation, retries/timeouts, monitoring, and metric-gated model deployment, and iterates closely with clinic staff using real call reviews.”
Ajay Rajakumar
Mid-level Full-Stack Developer specializing in Angular, Java, and MERN
“Full-stack developer with 4 years of experience and an MS in Computer Science who led frontend delivery for a large airline platform (booking, check-in, and payment flows) using Angular/TypeScript with a Java backend. Emphasizes quality at scale via SonarQube monitoring, E2E/regression testing, and iterative Agile collaboration with clients using Figma.”
SREEJA REDDY Konda
Mid-level AI/ML Engineer specializing in NLP, MLOps, and predictive analytics
“AI/ML Engineer at Fifth Third Bank who has shipped production fraud detection and risk analysis systems combining ML models with LLM-powered insights/explanations, including real-time monitoring, drift detection, and automated retraining under regulatory explainability constraints. Also built a hybrid-retrieval internal knowledge-base QA system (+20% top-5 relevance) and delivered a customer support chatbot that reduced first response time by 30% through strong stakeholder collaboration.”
Raden Ananta
Senior QA Engineer specializing in test automation and FinTech
“QA tester with consulting experience focused on payment systems, including scenario testing and automation using QF-Test. Has a business-impact mindset (prioritizes revenue-critical end-to-end flows) and has surfaced high-severity defects that required source code changes; not yet experienced with console game testing or platform certification requirements.”
Harshini Jonnala
Senior Backend Software Engineer specializing in distributed systems and cloud microservices
“Backend engineer with NTT Data experience building Java/Spring Boot services for product-data ingestion, including Kafka-based asynchronous pipelines and Redis read-through caching. Also built a personal RAG system deployed on Google Kubernetes Service using FastAPI, LangChain, and Pinecone with multi-tenant data isolation; holds a Master’s background in Machine Learning.”
Sowmya Kasu
Mid-Level Software Engineer specializing in Healthcare IT and cloud-native microservices
“Backend/ML engineer with healthcare experience at Kaiser Permanente building HIPAA-compliant Java/Spring Boot + GraphQL APIs integrated with Epic HealthConnect, including hands-on reliability/performance debugging using Prometheus/Grafana and resolver-level N+1 elimination. Also built an end-to-end malaria parasite detection ML feature (CNN/R-CNN) with evaluation, guardrails, and workflow integration, and has experience designing robust state-machine-based automation with retries, DLQs, and alerting.”
Bhavana Anna
Mid-level AI/ML Engineer specializing in fraud detection and Generative AI (RAG)
“AI/ML engineer who has shipped production LLM and ML systems, including a RAG pipeline that ingested ~500k insurance/client documents to help adjusters answer questions faster and more consistently. Experienced in handling messy real-world document formats, tuning retrieval/chunking, and reducing latency via vector search optimization, precomputed embeddings, and caching. Also built orchestrated fraud-detection deployment workflows using AWS Step Functions and SageMaker, and partners closely with non-technical operations teams on NLP automation.”
Mohana pavan Vankayala
Mid-level Java Full-Stack Developer specializing in microservices and AWS
“Full-stack engineer (HCL Tech) with 4 years building enterprise, high-throughput microservices on AWS/Azure using Java/Spring Boot and React. Demonstrated measurable performance gains (40% throughput) through Redis caching, deep SQL/query tuning, and Kafka-based async refactors, plus strong DevOps/observability practices with Jenkins/CloudFormation and Datadog/Splunk.”
sai Pavan
Mid-level AI/ML Engineer specializing in MLOps, NLP, and real-time ML pipelines
“Built a production, real-time insurance claims document-understanding and fraud-detection pipeline using TensorFlow + fine-tuned BERT, deployed on AWS (SageMaker/Lambda/API Gateway) with automated retraining via MLflow and Jenkins. Addressed noisy documents and latency using augmentation and model distillation (3x faster), cutting claims ops manual review by ~50% and reducing fraudulent payouts.”
Allen Saunders
Senior DevOps/Solutions Engineer specializing in CI/CD, cloud platforms, and API integrations
“Solutions Architect with 5+ years leading pre- and post-sales engagements, focused on taking complex tooling from test/prototype to secure production through a structured discovery-to-deployment approach. Experienced in LLM workflow troubleshooting using tools like Langfuse/Gopher and in developer enablement via concise, hands-on workshops (e.g., Jenkins on Kubernetes at scale). Has navigated internal and external blockers to drive adoption and keep enterprise deals moving (including a Jenkins sale to Love's).”
Austin Near
Mid-Level Software Engineer specializing in full-stack and backend systems
“Full-stack JavaScript developer in small-company environments building PCB manufacturing web tooling. Owned and delivered blob-storage upload/download infrastructure (including an internal developer library) and a training/compliance tracking tool. Implemented secure, broadly compatible SSO for a customer portal under a <1 month deadline tied to an 8-figure customer deal, despite having no prior authentication experience.”
Teja Babu Mandaloju
Mid-level Data Scientist/MLOps Engineer specializing in NLP, GenAI, and cloud ML platforms
“AI/ML engineer who led production deployment of a multimodal (text/video/image) RAG system on GCP using Gemini 2.5 + Vertex AI Vector Search, scaling to 10M+ documents with sub-second latency and +40% retrieval accuracy. Strong MLOps/orchestration background (Kubernetes, CI/CD, Airflow, MLflow) with proven impact on reliability (75% fewer incidents) and deployment speed (92% faster), plus experience delivering explainable ML (XGBoost + SHAP + Tableau) to non-technical retail stakeholders.”
Srinandh Reddy
Mid-Level Software Engineer specializing in backend, cloud, and event-driven systems
“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”
Nicholas Kim
Entry-Level Software Engineer specializing in full-stack and backend development
“Full-stack developer who built a workout tracker feature end-to-end on the PERN stack (Postgres/Express/React), including relational schema design, REST APIs, and optimistic UI updates. Also has Next.js App Router experience (dynamic routes, SSG/React Server Components) and a strong quality mindset from Boston Scientific, where they used TDD to support clinically sound ECG analysis software and drove backend test coverage to 97%.”
Aarushi Mahajan
Junior AI/ML Engineer specializing in LLMs, RAG, and information retrieval
“Internship experience shipping production AI systems: built an end-to-end RAG platform (Python/FastAPI + LangChain/LangGraph + vector search) to answer support questions from unstructured internal docs, with a strong focus on hallucination prevention through confidence gating and rigorous offline/online evaluation. Also delivered an AI-driven personalization/analytics feature using an unsupervised clustering pipeline, iterating with PMs to align statistically strong clusters with actionable business segmentation.”
Sai Bandaru
Mid-level Machine Learning Engineer specializing in fraud detection and LLM systems
“At FiVerity, built and deployed a production LLM/RAG-based Information Gathering Tool for credit union fraud analysts that generates auditable investigation summaries from verified evidence. Focused on high-stakes constraints—hallucination prevention, cross-entity leakage controls, compliance/PII-safe monitoring, and latency—while also shipping customer-facing agentic workflows using CrewAI and LangGraph in close partnership with fraud and compliance stakeholders.”