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Vetted SQL Professionals
Pre-screened and vetted.
DEDEEPYA PALAKURTHI
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise MLOps
“Backend engineer who built an AI-driven "Smart Feedback Analyzer" API (Flask → FastAPI) that processes user feedback with NLP (Hugging Face + OpenAI) and returns structured insights. Demonstrates strong production-minded architecture: stateless services, Cloud Run + Docker deployment, Redis/Celery background processing, and Postgres/SQLAlchemy performance tuning (EXPLAIN ANALYZE, indexing, N+1 fixes), plus multi-tenant data isolation via JWT/API-key derived tenant IDs.”
PRAJU KUMAR
Mid-level Full-Stack Developer specializing in Java/Spring microservices and React/Angular
“Full-stack engineer with hands-on production experience building real-time customer-facing features (order tracking + push notifications) across React/React Native and Node/Spring Boot with Postgres/MySQL. Demonstrates strong reliability patterns (transactional outbox, background workers, idempotent webhook ingestion) and has deployed/operated systems on AWS (ECS/Fargate/ALB, CloudWatch, CodePipeline) with structured observability and environment separation.”
Affan Arif Khamse
Junior Software Engineer specializing in AI assistants and cloud-native backend systems
“Founding engineer at Novum AI building a real-time call analytics/suggestion backend (transcription + sentiment/tone + context retrieval) using a serverless architecture. Drove major latency improvements (about 4s down to sub-1.5s) and has practical experience hardening production APIs (FastAPI/Pydantic, auth with Cognito/Redis) and payment systems (Stripe) by surfacing overlooked subscription and multi-tenant billing edge cases.”
HARI ANDE
Junior Software Engineer specializing in backend microservices and GenAI automation
“Built and productionized an LLM/RAG-based credit case triage system that indexes credit bureau narratives and delivers structured, source-linked summaries for analysts. Emphasizes production reliability (data masking, human-in-the-loop review, abstention/fallbacks, monitoring) and reports >99% uptime plus ~30% efficiency gains, with iterative improvements driven by offline/online evaluation and schema-aware validation.”
Meenakshi Gurrala
Mid-level Java Full-Stack Developer specializing in cloud-native microservices and React
“Full-stack engineer with hands-on ownership of real-time, Kafka-driven systems in production, spanning React/TypeScript frontends, Spring Boot/Node backends, and AWS (EKS/ECS/EC2) operations. Notable for modernizing legacy batch workflows into event-driven architectures with measurable impact (35% faster risk calculations, 30% better accuracy) and scaling to 2x volume using reliability patterns like idempotency, retries, and staged rollouts.”
Ramcharan SreenivasaReddy
Mid-level Full-Stack Developer specializing in FinTech platforms and cloud-native microservices
“Backend/platform-focused Python engineer who has owned FastAPI services with Postgres/SQLAlchemy and production-grade auth (JWT + RBAC). Experienced deploying and operating microservices on Kubernetes with GitOps (ArgoCD), HPA tuning, and Prometheus/Grafana monitoring, plus hands-on cloud-to-on-prem migrations and Kafka-based real-time streaming pipelines.”
Rupak Chand
Junior ML Data Associate specializing in AI training data and LLM prompt evaluation
“Applied ML/embodied AI practitioner who built an on-device gesture-control system for smart-home lights using Raspberry Pi + camera, focusing on privacy-preserving real-time inference and hardware-constrained optimization (async pipeline + TF Lite INT8). Also made a high-impact architecture decision for an ML content evaluation/QA pipeline processing millions of annotated text samples weekly, reducing batch runtime from ~6 hours to ~40 minutes while lowering compute cost.”
Fatemeh Taghvaei
Junior AI/ML Engineer and Instructor specializing in deep learning, computer vision, and NLP
“Computer-vision practitioner and educator who built a real-time license plate recognition system (OpenCV/Python + KNN) optimized to run on a Raspberry Pi with camera integration. Also designs hands-on deep learning coursework, incorporating recent transformer-based vision research (Vision Transformers) into practical labs on real datasets.”
Husayn El Sharif
Senior Data Scientist specializing in geospatial ML and environmental analytics
“Applied ML practitioner who deployed a near-real-time water-quality monitoring tool for Gwinnett County by fusing ESA satellite imagery with in-situ measurements to predict chlorophyll-A and support early warnings for harmful algal blooms. Also working on a multimodal deep-learning project combining skin lesion images with patient tabular/text data (TensorFlow, embeddings) to predict melanoma risk.”
Nandini Reinthala
Mid-Level Full-Stack Python Developer specializing in AI and data platforms
“Full-stack engineer who builds TypeScript/React SPAs on Python (Flask/FastAPI) backends and has hands-on experience integrating AI components (Azure OpenAI, LangChain, vector databases) into user workflows. Has built internal AI-enabled dashboards/search tools for analysts and business users, emphasizing typed API contracts, CI/CD-driven quality, and microservices reliability patterns (monitoring, retries, idempotency) at scale.”
Lokesh Jain
Senior Data Engineer specializing in cloud data platforms and ML pipelines
“Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.”
Manikanta Kopparapu
Mid-Level Full-Stack Software Engineer specializing in cloud-native web applications
“Full-stack engineer who has owned customer-facing and internal web portals end-to-end (API, database, React UI, and deployment). Experienced designing multi-service architectures with Node/Express and Java/Spring Boot plus RabbitMQ/Kafka messaging, emphasizing contract/versioning discipline, observability, and operational tooling that measurably reduces support load and manual work.”
Maxwell Meyer
Junior Integration Engineer specializing in healthcare interoperability (HL7 v2/FHIR)
“Integration engineer at Epic focused on healthcare interoperability, including complex radiology integrations (orders/results) spanning more than a dozen downstream systems and PACS vendors. Experienced coordinating clinical Radiant teams, interface analysts, and networking teams to scope workflows, route/transform messages via an interface engine, and troubleshoot intermittent production issues using structured isolation and live testing.”
Ketan Verma
Junior Applied AI Engineer specializing in data pipelines and ML systems
“Built an end-to-end wafer-data anomaly detection and reporting system at Samsung using PySpark, Random Forest models, SQL, and Grafana to help engineers track faults and take corrective action. Also has strong UX prototyping and validation practices in Figma plus hands-on front-end/full-stack experience (HTML/CSS/TypeScript), including a student project recognized as best design out of 25 teams, and early-stage startup experience pivoting a product based on user interviews into a real-time in-context feedback overlay.”
Nisarg Shah
Junior Machine Learning Engineer specializing in geospatial analytics and computer vision
“Built and evolved a geospatial ETL + API platform that processes pixel-wise satellite imagery in PostgreSQL/PostGIS into low-latency farm-level time-series metrics for an interactive dashboard, using precomputed hotspot analysis to reduce latency by 75–80%. Experienced in FastAPI-style API contract design (OpenAPI), caching, server-side filtering/compression, and production-minded security patterns (RBAC, session-derived authorization, password hashing) with disciplined rollback/versioning practices.”
Tejas Kolpek
Mid-level Solutions Architect/Engineer specializing in AI and data integrations
“Solutions Engineer specializing in taking LLM copilots from demo to production, with a strong emphasis on enterprise security (RBAC/OAuth), grounded RAG behavior (cite-or-refuse), and operational readiness (eval loops, logging, runbooks). Experienced in real-time diagnosis of agentic/LLM workflow failures and in partnering with Sales/CS to run integration-first POCs that clear security and reliability concerns and accelerate rollout.”
Harikiran Jangam
Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG systems
“Backend engineer who built and evolved a PHI-compliant RAG system (FastAPI + LangChain + embeddings/FAISS) for internal document search and summarization, delivering <400ms p95 latency at ~2,500 daily requests and measurable impact (30% faster investigations, +17% retrieval relevance). Demonstrates strong security and rollout discipline (RBAC/RLS/JWT, redaction/audits, shadow mode, dual writes, canaries) and a focus on reducing hallucination risk via grounded guardrails and confidence-based fallbacks.”
Pree Simphliphan
Intern Software Engineer specializing in robotics, embedded systems, and AI
“Senior design robotics engineer on a "Grocery Robot" project selected for the final round of the $10K SICK Challenge, owning ROS2 system design and behavior-tree-based task orchestration across multiple independently developed modules. Also implemented I2C/ESP32 collision avoidance, IK control for a robotic arm, and a Node.js ordering system, with additional research experience using RPLIDAR-based SLAM.”
SAI NAGINI VALLURUPALLI
Junior Full-Stack Java Developer specializing in Spring Boot microservices and React
“Full-stack Java/Spring Boot + React engineer (3–4 years) who built an end-to-end smart employee management system and a data analytics dashboard handling millions of daily transactional records. Emphasizes scalable layered REST API design, secure microservices practices (Spring Security, JWT/OAuth2), and performant React state/data patterns (Redux Toolkit + RTK Query) for large datasets and role-based views.”
Sai Rahul Dasari
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and healthcare RAG systems
“Built and deployed a production clinical claim validation RAG system at GE HealthCare that automated nurses’ patient-history/claims checks, cutting manual review time by ~65%. Designed the full stack (retrieval, embeddings, Pinecone, prompt/verification guardrails, FastAPI backend) with PHI-compliant anonymization via NER and orchestrated pipelines using Airflow, Azure ML Pipelines, and MLflow with drift monitoring.”
Surya Vamshi Sriperambudooru
Mid-level AI Engineer specializing in healthcare claims analytics and RAG copilots
“Built a production "appeals co-pilot" for a healthcare claims appeals team, combining an XGBoost/logistic ranking model with a Python/LangChain RAG stack (FAISS + Mistral 7B) to surface high-probability appeal wins and speed policy-grounded drafting. Emphasizes reliability and trust: hybrid retrieval with metadata routing, citation/eval scripts, guardrails, and an explainability layer that non-technical stakeholders could understand and override.”
Pranita Agrawal
Mid-level Software Engineer specializing in Java microservices and AWS
“TypeScript backend/full-stack engineer who owned an internal business workflow platform end-to-end in production, including API/data design, relational DB integration, and enterprise integrations. Has hands-on experience operating workflow processing services with Kafka-style event-driven patterns, idempotency, exponential backoff retries, dead-letter queues, and strong observability, plus API design with OpenAPI/Swagger and token-based auth.”
Rajesh Sivakumar
Senior Software Engineering Manager specializing in cloud-native distributed systems (FinTech & Healthcare)
“Engineering leader/player-coach who has led 40+ developers across multiple teams on large financial services web applications (Wells Fargo) and previously delivered a banking mobile app MVP in 6 months with a junior team by setting patterns and CI/CD foundations. Strong in production reliability practices (Splunk monitoring, feature flags, throttled rollouts) and has driven measurable quality/velocity wins, including a 60% faster E2E test framework and a rapid 2-day hotfix during a React 16→18 migration.”