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Vetted Oracle Database Professionals
Pre-screened and vetted.
Mid-level Software Engineer specializing in full-stack AI and LLM applications
Intern AI Software Engineer specializing in LLM inference optimization and model compression
Mid-level Full-Stack Engineer specializing in Python microservices and cloud automation
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Senior Full-Stack Software Engineer specializing in scalable microservices and cloud platforms
Principal Systems & Software Engineer specializing in IVD/medical device compliance and genomics
Mid-level Full-Stack Developer specializing in AWS modernization and Java/Angular
Senior Software Engineer specializing in data engineering, BI analytics, and AI/ML
Senior Full-Stack Engineer specializing in AI-powered enterprise applications
Staff Software Engineer specializing in backend platforms and FinTech/SaaS systems
Principal Software Engineer specializing in distributed systems and cloud microservices
Pavan Devulapalle
Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development
“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”
Sanketh Reddy
Senior Data Engineer specializing in cloud data platforms and large-scale ETL
“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”
Poorna Pedapudi
Mid-Level Software Engineer specializing in distributed backend systems and cloud-native microservices
“Software engineer focused on data platforms and applied LLM systems: built an internal data quality monitoring layer to catch silent data drift and iterated post-launch after finding ~30% false-positive alerts, reducing noise via dynamic baselines and improved structured logging. Also shipped a production RAG-based internal knowledge assistant over Jira/Confluence with citations, confidence-based fallbacks, and nightly automated evals to prevent regressions.”
Pujan Thapa
Mid-level AI Engineer specializing in LLM applications and enterprise automation
“Engineer with a notably mature AI-native development process: uses Claude/Claude Code in a test-first, iterative workflow and has led multi-agent builds across frontend, backend, and testing. Most notably, they led development of an AI voice agent platform, creating custom agent skills and enforcing clear architectural boundaries to deliver a stable, scalable system.”
Rafeeq Mohammad
Senior Full-Stack Engineer specializing in Java microservices and FinTech
“Backend engineer with experience at JPMorgan Chase and Walgreens, owning transaction-processing and prescription data flow systems in regulated environments. Brings strong hands-on depth in Spring Boot microservices, Kafka, Redis, Kubernetes, observability, and production incident resolution, plus practical experience integrating OpenAI-powered workflows with validation and fallback safeguards.”
Rohith M
Mid-level Full-Stack Developer specializing in AWS serverless and Java/Spring
“Built and shipped a production generative-AI recipe feature on AWS serverless (Lambda + Bedrock), evolving it post-launch from fully AI-generated outputs to user-guided structured generation based on real usage patterns and system metrics. Emphasizes reliability via prompt constraints plus deterministic validation, with automated/human eval loops and CloudWatch-based observability to manage latency, cost, and output consistency.”