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Vetted AWS Professionals
Pre-screened and vetted.
Samuel Audu
Staff Platform Engineer specializing in multi-cloud platforms and internal developer portals
“Infrastructure reliability/capacity-focused engineer with hands-on IBM Power/AIX (LPAR/DLPAR, HMC, VIOS) performance troubleshooting and modern cloud-native delivery experience. Built production CI/CD and Terraform-managed AWS/EKS environments, and has led real incident recoveries spanning Kubernetes autoscaling and AWS quota constraints with concrete RCA and prevention improvements.”
Sahithya Godishala
Mid-level AI/ML Engineer specializing in GenAI, LLMs, RAG, and MLOps
“Built and deployed a production LLM-powered RAG document intelligence/Q&A system for healthcare prior authorization, reducing manual medical document review time and improving decision efficiency. Strong in end-to-end LLM application engineering (LangChain/LangGraph), retrieval quality improvements (hybrid search, embedding tuning, chunking strategies), and rigorous evaluation/monitoring for reliability.”
Divya Sai Nagabhairu
Mid-Level Full-Stack Developer specializing in Java/Spring microservices and cloud platforms
“Full-stack engineer with e-commerce experience who shipped and owned an order history dashboard using Next.js App Router/TypeScript, combining server components for SEO/perf with client-side interactivity via React Query. Has backend reliability experience (Temporal order-processing workflows, Postgres modeling/indexing, and payment API idempotency keys), and emphasizes production stability, observability, and zero-incident launches.”
Yu Liu
Senior Big Data Engineer specializing in AML/KYC compliance and cloud data platforms
“Data engineer with experience delivering an end-to-end pipeline handling ~3.5TB in a star-schema setup (fact + dimensions) and producing business-facing tables in Hive/Spark. Identified and resolved UAT-reported duplicate issues caused by joins through root-cause analysis, and also built automation to run Spark SQL metrics on weekly/monthly/quarterly cadences and distribute results to users.”
Mahesh Kumar Duvvuri
Senior Full-Stack Software Engineer specializing in microservices and cloud-native systems
“Backend/infra engineer with experience across Nestle, J.P. Morgan, and Capgemini, combining ML systems work (YOLOv8/PyTorch object detection with TFLite edge deployment) with production-grade cloud/Kubernetes operations. Has delivered measurable impact via AWS migrations (25% cost reduction, 99.9% availability), microservice modernization (35% faster processing), and low-latency Kafka streaming for financial dashboards (<100ms) using DLQs and idempotent consumers.”
Arifullah Suleman
Principal Infrastructure Architect specializing in hybrid cloud, data center modernization, and resilience
“Windows/VMware infrastructure project lead with experience managing 3,000+ servers across large enterprise environments (mentions Pfizerco, American Express, and FedEx). Focused on performance troubleshooting and stability using monitoring tools, plus security hardening and dependency/latency evaluation during on-prem to AWS/Azure hybrid migrations.”
Joseph Orisino
Senior Longform Video Editor specializing in YouTube-style storytelling and post-production leadership
“Senior editor/post-production supervisor with extensive Premiere + After Effects experience across major media brands (Yahoo Finance, Thrillist, Yahoo News/Katie Couric) and current work producing a video suite for SkinCeuticals (L'Oréal). Known for building scalable editorial workflows (style guides, review processes) and delivering retention-focused longform YouTube edits with strong cross-functional coordination through color, audio, graphics, and social versioning.”
Edward Robinson-Adams
Executive cybersecurity and AI leader, CEO/co-founder specializing in enterprise SaaS and strategy
“Operator who took a seed-funded university spin-off in cybersecurity from zero revenue and heavy losses to profitability and industry leadership, while building the full internal ops stack (HR/payroll/benefits/401k) and the initial GTM engine (Salesforce/HubSpot, SPIN + MEDPICC). Personally led fundraising across 30+ VC pitches, raising $11.2M total and delivering $98M returned to investors to date, with additional upside from a subsequent spin-off.”
Abhinav Gupta
Junior Machine Learning Engineer specializing in LLMs and applied data science
“Built and shipped multiple production AI systems, including Auto DocGen (LLM-generated OpenAPI docs kept in sync via AST diffs, schema-constrained generation, and CI/CD on Render) and a multimodal sign-language recognition pipeline at USC orchestrated with FastAPI, MediaPipe, and PyTorch. Also partnered with Esri’s non-technical community team to fine-tune an LLaMA-based spam classifier with a review UI, cutting moderation time by 70%.”
Ajay Madhusudhan Thumala
Junior Software Engineer specializing in data engineering and LLM applications
“Computer science engineer and master’s graduate who independently built a mechatronics-heavy capstone prototype: a smartphone concept for deafblind users using micro-actuator arrays for braille reading. Also has platform engineering experience at Quantiphi, deploying webhooks to Kubernetes and implementing GitOps-based CI/CD using AWS CodeCommit/CodeBuild and ECR.”
Nikhil Soni
Junior AI/ML Engineer specializing in LLM systems and retrieval-augmented generation
“Built and deployed a production LLM-powered market intelligence and decision-support platform for noisy, real-time financial data, using a high-throughput embedding + vector DB RAG architecture to reduce hallucinations while keeping latency and cost low. Operated it at scale with GPU-backed inference (continuous batching/quantization), FastAPI on Kubernetes, and Airflow-orchestrated ingestion/embedding/retraining workflows, with strong schema-based reliability and monitoring.”
Ruthvik Bacha
Mid-level Data Engineer specializing in financial data pipelines and reliability
“Systems/robotics-oriented software engineer focused on real-time orchestration and reliability: built a central control layer coordinating multiple concurrent agents with safe state machines, failure isolation, and recovery. Has hands-on ROS/ROS 2 integration experience in simulation (DDS/QoS, lifecycle, nodes in Python/C++) and emphasizes observability (structured JSON logs, correlation IDs) and low-latency control-loop performance under load.”
Jen-Hung Chang
Mid-level Software Engineer specializing in cloud infrastructure and distributed systems
“Backend/platform engineer who built an AI RAG system on FastAPI/Postgres/AWS with 10+ microservices, vector search optimization (ANN + two-stage re-ranking), and GitOps-driven CI/CD that cut deploy time from hours to minutes. Also deployed Java identity services on Kubernetes at TSMC for 200K+ users using ArgoCD/Azure Pipelines, and built a reliable real-time IoT pipeline (MQTT/Node/MongoDB) with strong consistency controls.”
Nishantkumar Asodariya
Mid-level Supply Chain Analyst specializing in global logistics automation and forecasting
“Built and shipped a production LLM-powered recruiting workflow that ranks resumes against job descriptions, generates evidence-based justifications, and finds "hidden fit" candidates using embeddings + RAG. Demonstrates strong production engineering around hallucination control, latency, and predictable LLM cost management (budget checks, top-K pruning, tenant caps), plus orchestration experience with Airflow/Prefect/Kubernetes and a structured evaluation/monitoring methodology for AI agents.”
Venkata Phaneendra
Mid-Level Java Full-Stack Developer specializing in cloud-native microservices
“Full-stack engineer with production ownership across React/TypeScript, Node/Express, and Postgres, including zero-downtime releases and rollbackable migrations. Demonstrated measurable performance wins (20% response-time reduction) through DB query profiling and batching, plus hands-on AWS operations (ECS/Lambda/CloudWatch) and reliability patterns for ETL (retries, DLQs, idempotency). Experience shipping microservices quickly in ambiguous, fast-paced environments (Deloitte).”
Jhansi Bendi
Senior Software Engineer specializing in cloud-native microservices and event-driven systems
“Senior engineer/tech lead with 18+ years building large-scale distributed applications, specializing in performance and reliability improvements. Recently owned multiple apps on an email personalization team, shipping major optimizations (including a push-update feature and audience-count architecture redesign) that reportedly lifted system performance from ~50% to ~99% while also leading code standards, reviews, and mentoring.”
Poojitha MaheshShyla
Mid-level Java Backend Developer specializing in cloud-native microservices
“Backend-leaning full-stack engineer with Walmart experience building and operating high-volume media upload and processing systems. Strong in Java/Spring Boot, Postgres performance tuning (EXPLAIN/ANALYZE), and durable workflows using Kafka/Spring Batch with retries and idempotency, plus production ownership via monitoring and optimization; familiar with Next.js/TypeScript and modern React performance patterns.”
Subbu Paravatareddy
Engineering Leader specializing in cloud modernization and AI/ML integration
“Player-coach engineering leader focused on buyer/distribution product lines, building scalable purchasing/planning frameworks and modernizing workflows. Drove performance and reliability improvements via queue-based async architectures, external API redundancy, and CI/CD automation, and has led production incident response (cache-related) with follow-up playbooks and monitoring. Experienced in high-growth/startup environments, combining hands-on delivery with mentoring, 1:1s, and performance coaching.”
Manasa Mangipudi
Mid-level Machine Learning Engineer specializing in NLP and computer vision
“AI/ML engineer with production experience building an LLM-powered resume-to-job matching and feedback product using RAG, with a strong focus on latency, hallucination control, and scalable deployment. Experienced orchestrating ML inference and backend services on Kubernetes and applying rigorous evaluation/guardrail practices; also partnered with business/product stakeholders at Walmart to improve an NLP-based supplier support system.”
Jeff Cushler
Executive Technology & Product Leader specializing in Healthcare IT, SaaS, and Cloud Transformation
“Startup product/enterprise-stack builder who helped take Ventric Health from R&D to a market-launched healthcare product in 2024, operating in a $34M-raised, revenue-generating model leveraging Medicare C reimbursement through providers. Previously drove adoption of an integrated K-12 digital learning platform distributed to 100+ institutions over two years, with reported improvements in test scores.”
Daniel Panrong Dai
Junior Software Engineer specializing in AI and full-stack development
“Consulting-background AI practitioner who led a production LLM pipeline on Snowflake Cortex to map hundreds of thousands of messy OCR/form-based contract fields into standardized Salesforce fields, including confidence scoring and an LLM-driven feedback loop. Strong focus on real-world constraints—token limits, cost control, and evaluation without ground truth—paired with frequent stakeholder-facing progress reporting.”
Bhanu Prakash Reddy Dakilli
Mid-level Data Engineer specializing in Azure ETL/ELT and data warehousing
“Data engineer who has owned end-to-end production pipelines for customer transaction data (~2–5 GB/day) using Python/PySpark/SQL and Airflow, delivering major reliability and speed gains (70% faster reporting; 60–70% fewer data issues). Also built a daily external web-scraping system with anti-bot handling and safe, idempotent Airflow-driven backfills, plus a Python data API optimized with indexing/caching and tested for correctness.”
Sri Harshitha Yannam
Junior Software Engineer specializing in AI/ML and cloud platforms
“LLM/agent engineer who shipped a production "Memory Assistant" at HydroX AI, building a LangChain/LlamaIndex RAG memory pipeline on ChromaDB/FAISS with robust fallbacks (BERT/BART), prompt-injection mitigation, and 99.9% uptime monitoring. Also built a multi-step customer support agent using Rasa + OpenAI Assistants API with structured tool calling, guardrails, and human-in-the-loop escalation, and has experience hardening agents against messy ERP data via Pydantic validation, idempotency, and transactional outbox patterns.”