Vetted Single Sign-On (SSO) Professionals

Balaji Vellaluru

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in full-stack and computer vision systems

Chicago, IL3y exp

“Built D.O.C.T.O.R, a 0-to-1 anatomy learning platform with 450+ 3D models that reached 6,500+ users, saved $850K versus a costly alternative, and was featured in a University of Illinois Chicago news article. The candidate combines product initiative with hands-on full-stack execution, spanning React/Three.js, databases, auth, analytics, and AI workflow automation side projects.”

“Full-stack web engineer with experience owning major e-commerce platforms like FultonFishMarket.com and USESI.com, including logistics-heavy B2B/B2C systems at million-user scale. Also built Django-based cloud connectivity for 3D printers via OctoPrint plugins, combining device APIs, payment integrations, and AWS container deployment. Demonstrates strong performance optimization skills and the ability to lead ambiguous platform features from process discovery through stakeholder-reviewed release.”

“Built and productionized an LLM-enhanced version of the WeDAA platform to auto-generate microservice architecture diagrams and support code generation from user prompts, including a practical solution for non-overlapping canvas object placement via coordinate templates. Experienced in diagnosing agentic workflow failures using AWS Strands agents with feature-flagged debug logging, and frequently supports sales through tailored demos and POCs to drive adoption.”

“Project/program manager with senior-level ownership across SaaS implementations, cloud migrations, AI agents, and DevOps initiatives. Notably led an Azure AI Studio-based AI analysis tool from start to finish and managed an enterprise healthcare technology portfolio with interdependent AI, data extraction, Copilot, and web application projects.”

“Salesforce admin/developer with 3-4 years of experience spanning admin fundamentals through Apex, LWC, integrations, and Experience Cloud. Particularly strong in Service Cloud and case management optimization, including a redesign that cut manual effort by 50-60% while improving reporting accuracy and response times.”

“Built and shipped production AI search and RAG features for a university portal, including an embeddings-based semantic search layer and a documentation-grounded assistant with citations and anti-hallucination prompting. Also developed scalable, reliable data pipelines integrating Google Ads/GA4/Meta APIs for automated reporting, with strong focus on evaluation loops and retrieval quality improvements (hybrid search, chunking, query-log driven iteration).”

Ibrahim Tantawy

Screened

Senior Back-End PHP Developer specializing in scalable web APIs

Dubai, UAE7y exp

“Full-stack PHP/Laravel and Vue.js developer with experience spanning startup e-learning, e-commerce, and a B2B SaaS logistics platform. Particularly notable for integrating Stripe early in their career, improving MySQL performance with indexing, and handling client-specific GPS integrations for enterprise transportation customers such as Coca-Cola, Pepsi, and Emirates Logistics.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”

Taruni Reddy Ampojwala

Screened

Mid-level GenAI Engineer specializing in LLM agents and RAG systems

Brooklyn, NY4y exp

“Built and deployed a production RAG-based LLM assistant that answers day-to-day operational questions from internal PDFs/SOPs, with strong emphasis on data consistency (metadata versioning, confidence thresholds, conflict handling) and low-latency retrieval at scale. Experienced designing and orchestrating multi-agent LLM workflows (retrieval/validation/generation) and pipeline orchestration for ingestion/embedding/vector-store updates, plus iterative delivery with non-technical operations/business stakeholders.”

“Built and shipped a production LLM-powered incident response agent for a microservices platform, automating alert triage and safe remediation recommendations with strong guardrails (RAG grounding, structured JSON outputs, rule-based validation, and human-in-the-loop). Implemented state-machine orchestration (Redis/Kafka), comprehensive eval/monitoring, and an error categorization pipeline that cut hallucination errors ~40% and reduced MTTR ~30%.”

chaitra putumbaka

Screened

Junior Data Scientist and Software Engineer specializing in ML and cloud applications

Leesburg, VA2y exp

“Backend engineer currently at Intuit Mailchimp working on transactional messaging infrastructure, with hands-on experience improving backlog-count latency through database redesign and sharding. Also has practical experience integrating Mailchimp capabilities into MCP-based AI workflows and previously worked on a financial-domain LLM chatbot using prompt design and RAG.”

“Full-stack engineer who has owned both institutional and personal products end-to-end, including Rutgers' myCommunity platform used by 70,000+ students. Particularly strong in production systems, data synchronization, authentication, and third-party API integrations, with a pragmatic approach to shipping, observability, and UI modernization.”

“Full-stack product engineer with hands-on ownership of both real-time product infrastructure and production AI systems. They shipped a notification platform that materially improved engagement and repeat purchases, and also built key layers of an AI support agent with strong reliability controls and user-centered UX improvements that boosted adoption.”