Vetted AWS CodePipeline Professionals

“LLM/RAG engineer who has shipped production systems in high-stakes domains (fraud analytics at Mastercard and security compliance as a CI/CD gate). Strong focus on reliability: hybrid retrieval for latency, citation-backed outputs for trust, and code-driven eval/regression pipelines using golden datasets. Also built scalable OCR-based ingestion for messy classroom artifacts (handwriting, PDFs, whiteboard photos) using Go/Python and cloud services.”

Ajay Madhusudhan Thumala

Screened

Junior Software Engineer specializing in data engineering and LLM applications

Irvine, CA1y exp

“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.”

Sanjana Duvva

Screened

Mid-level AI/ML Engineer specializing in Generative AI, LLMOps, and MLOps

5y exp

“Built and deployed an AWS-based LLM/RAG ticket triage and knowledge retrieval system (Pinecone/FAISS + Step Functions + MLflow) that cut support resolution time by 20%. Demonstrates strong production focus on hallucination reduction, PII security, and low-latency orchestration, with measurable evaluation improvements (e.g., ~25% grounding accuracy gain via re-ranking) and proven collaboration with support operations stakeholders.”

“Engineering leader/CTO-type with deep experience building and scaling a vehicle routing platform at Transdev On Demand, including a nationwide rollout to 22 US airports ahead of schedule. Drove engineering best practices (CI/CD, high test coverage, pair programming, automated deployments) and led a multi-tenant architectural upgrade to expand the routing engine to additional business lines and external customers.”

“Backend engineer who built and owned an AI-powered SMS survey platform for a nonprofit serving at-risk communities (internet-limited users), using Cloudflare Workers + Twilio and a state-machine survey engine. Scaled it to ~10k active users with near-zero downtime, added English/Spanish support, and iteratively improved LLM behavior (Claude 3.7 Sonnet) to handle nuanced, real-world SMS responses reliably.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

“Software engineer with strong end-to-end ownership of search and listing systems (React/TypeScript frontend with Node.js + Spring Boot backends), focused on shipping fast while managing risk via feature flags, testing, and metrics. Demonstrated measurable UX/performance wins (reduced latency and search abandonment) and built internal observability tooling (dashboard + alerts) that improved incident response. Experienced with microservices reliability patterns including idempotency and dead-letter queues.”

“Data engineer at Capital One building AWS-based real-time and batch pipelines and backend data services for financial/fraud use cases. Has owned end-to-end pipelines processing millions of records/day, implemented dbt/Great Expectations quality gates, and tuned Redshift/Snowflake workloads (cutting query latency ~22–25% and reducing pipeline failures ~30–40%) while supporting 15+ downstream consumers.”

jiayu Zhao

Screened

Junior Quantitative Analyst and Full-Stack Engineer specializing in FinTech and web platforms

Chicago, IL6y exp

“Backend/distributed-systems engineer with AI infrastructure experience who built an AI-driven video generation platform, focusing on an asynchronous FastAPI-based orchestration layer between user APIs and heavy inference services. Strong in production instrumentation and latency/concurrency optimization; actively learning ROS 2 but has not yet worked on physical robotics or ROS-based deployments.”

Vamsi Reddy

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial ML systems

Nashville, TN5y exp

“ML/AI engineer with hands-on experience shipping both predictive healthcare models and clinical GenAI assistants into production. They combine strong MLOps depth across Azure and AWS with healthcare-specific safety thinking, including PHI guardrails, retrieval grounding, and production monitoring, and they also built internal Python tooling for fraud ML workflows at Capital One.”

“Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.”