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Vetted Azure Functions Professionals
Pre-screened and vetted.
Mid-level Full-Stack Developer specializing in React, .NET, and cloud platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native healthcare and FinTech systems
Mid-level Machine Learning Engineer specializing in MLOps and Generative AI
Mid-Level Full-Stack Software Developer specializing in Healthcare IT and FinTech
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Senior Software Engineer specializing in full-stack .NET and AI/ML systems
Mid-level Software Engineer specializing in cloud-native microservices and Healthcare IT
Mid-level Full-Stack .NET Developer specializing in Angular, Azure, and AI integrations
Senior .NET Developer specializing in cloud-native microservices and modern web apps
Senior Full-Stack Developer specializing in Python, Django, React, and cloud-native SaaS
Shreevershith Kollabettu
Mid-level AI Engineer specializing in LLMs, agentic systems, and MLOps
“AI-focused engineer with Infosys experience building Azure/.NET chatbot applications and recent hands-on work with FastAPI/LangChain. Built a hackathon multi-agent legal counsel system showcasing agent orchestration, and emphasizes production readiness via Docker, GitHub Actions CI/CD, pytest automation, and adversarial simulations for auditable AI behavior. No direct robotics/ROS experience to date.”
Mark Wlodawski
Senior Unity Developer specializing in AI/LLM systems and multiplayer VR
“Backend/data engineer focused on AWS-native Python systems: built a FastAPI microservice on ECS/Fargate serving real-time analytics at millions of daily requests with strong reliability (OAuth2/JWT, retries/timeouts, correlation IDs) and autoscaling. Also delivered Glue/PySpark ETL pipelines to curated S3 Parquet/Athena with schema evolution + data quality controls, owned Airflow pipeline incidents, and has a track record of measurable performance and cost optimizations (e.g., ~80%+ query latency reduction; reduced logging/NAT/Fargate spend).”
Tanya Rodrigues
Mid-level Software Engineer specializing in cloud-native AI and full-stack systems
“Application-focused software engineer working on AI-heavy products, with hands-on experience building end-to-end document processing, retrieval, and configurable workflow systems. Particularly strong in combining React/TypeScript UX, FastAPI/Postgres backend design, and LLM workflow reliability improvements through validation, prompt iteration, and reusable abstractions.”
Mid-level Backend Software Engineer specializing in Java microservices and Azure cloud
Mid-level Software Engineer specializing in full-stack web and cloud applications
Executive infrastructure and security leader specializing in multi-cloud enterprise architecture
Mid-level Software Engineer specializing in Python APIs, cloud, and AI/LLM integration
Mid-level Software Engineer specializing in FinTech and scalable backend systems
Senior .NET Full-Stack Developer specializing in cloud-native microservices
Executive Engineering Leader specializing in Product, Mobile, and SaaS platforms
Sravani Gangaraju
Mid-level AI/ML Engineer specializing in NLP, computer vision, and recommender systems
“Built and deployed a production NLP sentiment analysis system at Piper Sandler to turn noisy, finance-specific customer feedback into scalable insights. Demonstrates strong end-to-end MLOps: fine-tuning BERT, improving label quality, monitoring for language drift, and automating retraining/deployment with Airflow and Docker (plus Kubeflow exposure).”
Malli Karjuna
Mid-Level .NET Full-Stack Developer specializing in cloud-native web applications
“JavaScript engineer with open-source library contribution experience, including diagnosing a validation-related bug, shipping a tested fix, and improving documentation with practical examples and edge-case guidance to reduce repeated community questions. Emphasizes profiling-driven performance work, small safe refactors, and proactive ownership in fast-moving, unstructured teams.”
“Built and operated end-to-end legal-document data pipelines fed by hundreds of scraper sources, emphasizing data quality validation, reliability (CloudWatch monitoring/alerting, retries, backfills), and serving enriched legal data via serverless AWS APIs (Lambda/API Gateway). Experienced in keeping API contracts stable with additive versioning practices and shipping MVPs quickly with CI/CD and observability in place.”