Vetted AWS Lambda Professionals

Butchi Venkatesh Adari

Screened

Mid-level Machine Learning Engineer specializing in LLM platforms and robotic perception

NewYork, NY4y exp

“Built and shipped a production multi-agent personal financial assistant at AlphevaAI on AWS ECS, combining FastAPI microservices, Redis/SQS orchestration, and Pinecone-based hybrid RAG (semantic + BM25) to ground financial guidance. Improved routing accuracy with an embedding-based SetFit + logistic regression intent classifier feeding an LLM router, and optimized UX with live streaming plus cost controls via model tiering and caching.”

Shabari Vignesh

Screened

Mid-level Data Engineer specializing in cloud data platforms and AI agents

Santa Clara, CA6y exp

“Data/Backend engineer who has owned end-to-end merchant analytics systems on AWS: orchestrated multi-source ingestion (FISERV/Shopify/Clover) with Step Functions/Lambda, enforced strong data quality gates, and served curated datasets via Redshift and a FastAPI layer. Also built an early-stage Merchant Insights AI agent that converts natural language questions into SQL using OpenAI models, with full CI/CD and observability.”

Tejasri Alla

Screened

Mid-level Full-Stack Python Developer specializing in banking microservices

Northridge, CA5y exp

“Built and led production LLM-agent systems in enterprise environments (Simmons Bank, Mindtree), automating support ticket triage end-to-end with strong reliability engineering (99.9% uptime, Prometheus/Grafana, ECS autoscaling, CI/CD rollback). Demonstrated clear business impact (55% faster handling, SLA compliance 72%→96%, 800+ hours saved/month, +18% CSAT) and mature eval/feedback loops that improved extraction accuracy by 21%.”

Harika Reddymalle

Screened

Mid-Level Full-Stack Software Engineer specializing in backend automation and insurance systems

Dallas, TX4y exp

“Full-stack engineer with hands-on production ownership across Angular/.NET/SQL and React+TypeScript/Node/Postgres stacks, including CI/CD and AWS operations (EC2/ECS, RDS, S3, CloudWatch). Delivered an internal insurance document upload and tracking feature end-to-end, adding audit/history and async processing, then validated success through monitoring metrics and reduced support tickets. Comfortable shipping MVPs in ambiguous environments using feature flags, strong validation, and backward-compatible database migrations.”

AneeshReddy Kusa

Screened

Junior Full-Stack Software Engineer specializing in React and FinTech

Hyderabad, India2y exp

“Full-stack engineer with banking-domain experience (Cognizant/Kotak) building and optimizing high-usage transaction/account APIs on Spring Boot/Node/PostgreSQL in AWS/Docker, including peak-load performance fixes. Also built an end-to-end retail demand-forecasting feature during a master’s program, spanning data pipelines, ensemble models, dashboards, and operational guardrails like validation and fallbacks.”

Sanjana Akula

Screened

Senior Full-Stack Software Engineer specializing in cloud-native microservices and FinTech

New York, NY5y exp

“Front-end engineer with experience at Optum and Wells Fargo maintaining internal React/Angular component libraries and design-system-aligned UI modules used across multiple apps. Known for stabilizing shared libraries via semantic versioning, Jest test automation, and high-quality documentation, plus measurable performance wins (≈40% faster dashboard loads) through profiling-driven React and API optimizations.”

Snehitha Penumaka

Screened

Mid-level AI/ML Engineer specializing in predictive modeling and cloud ML pipelines

Dallas, TX3y exp

“LLM engineer/data engineer who has deployed production RAG systems for internal-document Q&A, building end-to-end ingestion, embedding, vector search, and FastAPI serving while actively reducing hallucinations and latency through rigorous retrieval tuning and caching. Also experienced in orchestrating cloud data pipelines (Airflow, AWS Glue, Azure Data Factory) and partnering with non-technical business teams to deliver AI solutions like automated document review.”

Sivapriya Rachakonda

Screened

Mid-Level Software Engineer specializing in cloud-native microservices on AWS and Kubernetes

Remote, USA5y exp

“Backend engineer who built a stateless Python/Flask service supporting a healthcare-document ETL pipeline, offloading heavy processing to Celery workers and adding strong observability (metrics, structured logs, audits). Demonstrates practical performance/reliability work: batch chunking, priority queues, autoscaling by queue depth/CPU, DLQ routing, and PostgreSQL tuning (indexes, pagination) to cut slow API responses. Also has experience deploying real-time ML classification via TensorFlow Serving behind a FastAPI wrapper and integrating models via REST/gRPC.”

Pravalika Kuppireddy

Screened

Mid-level AI/ML Engineer specializing in Generative AI and intelligent automation

4y exp

“LLM engineer who built and productionized a system to classify GitHub commits (performance vs non-performance) using zero-/few-shot approaches over commit messages and diffs, working at ~5M-record scale on multi-node NVIDIA GPUs. Experienced orchestrating end-to-end LLM pipelines with Airflow and GitHub Actions, and emphasizes reliability via testing, guardrails, and observability while collaborating closely with non-technical product stakeholders.”

Valeriy Filin

Screened

Senior Backend/Cloud Engineer specializing in IaC, SaaS platforms, and ML/Computer Vision

Aliso Viejo, CA19y exp

“Backend/infrastructure engineer with experience across API development (FastAPI/MySQL/SQLAlchemy), Kubernetes deployments, and large-scale data processing—built a Dockerized Python pipeline to pre-aggregate ~1B Graylog events for efficient querying. Has enterprise infrastructure automation background at Hewlett Packard Enterprise (Datafabric) using Terraform/Ansible with fail-fast and rollback practices, plus Kafka-based sensor streaming prototypes to Google Cloud with Java workers and autoscaling.”

Rahul Solleti

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and full-stack web apps

United States5y exp

“Backend/platform engineer focused on real-time financial fraud detection and transaction monitoring, building low-latency FastAPI + Kafka systems with strong reliability patterns (DLQs, idempotency) and cloud observability. Has hands-on Kubernetes delivery across AWS EKS and Azure AKS with automated CI/CD and GitOps-style deployments, plus experience migrating legacy C# / Java monoliths to containerized microservices using Terraform/ARM and zero-downtime rollout strategies.”

“Built and shipped a widely adopted, production-grade RAG internal search assistant that unified scattered engineering knowledge, deployed as a FastAPI service on Kubernetes with FAISS + LangChain. Demonstrates deep practical expertise in retrieval tuning (chunking, hybrid search, re-ranking) and in making LLM workflows reliable in production via guardrails, monitoring, and evaluation, plus strong cross-functional delivery with non-technical operations teams.”

“Founding/early engineer experience across Asante and a Series A startup (Adgency), shifting from data science/ML into owning production full-stack systems end-to-end. Built core product flows (registration, business profiles, map service), AWS-deployed gRPC microservices with CI/CD, and operated low-latency agent/video ad generation workflows with retries/fallbacks and PostHog-based observability.”

“Built a production LLM-assisted workflow for customer configuration data migrations, combining agentic parsing with deterministic validation and fail-safe pipeline design. Stands out for turning messy ERP and operational data into reliable, repeatable transformations while improving accuracy and cutting manual effort by more than 80%.”

“Software engineer who built JobIntel, an end-to-end Python ETL pipeline integrating ATS data from platforms like Greenhouse using Scrapy and FastAPI. Stands out for production reliability work: designing async fault-tolerant architecture, optimizing PostgreSQL write-heavy upserts, and building a Prometheus/Splunk observability stack that cut debugging from hours to minutes.”

“Built and deployed an end-to-end fintech product, FinSight, for bank statement analysis and financial Q&A using a production-style RAG architecture. Stands out for combining FastAPI, OpenAI embeddings, FAISS, hybrid SQL/vector retrieval, and practical reliability work like chunking optimization, validation, and low-latency performance tuning.”

“Full-stack engineer with startup-style ownership across backend, frontend, and AI systems, spanning Java/Spring, React, Node/TypeScript, and LLM-powered retrieval. Shipped a workspace intelligence layer using LangChain, OpenAI, and Pinecone to paying customers, while also improving core product metrics like workspace creation success (+30%), latency (450ms to 280ms), and deployment cycle time (-40%).”

Lucca Chantre

Screened

Intern Front-End Developer specializing in web and 3D graphics

Boston, MA0y exp

“Frontend candidate with unusually strong graphics-oriented experience, including React Three Fiber, Three.js, and WebGL. They have built interactive 3D UI behavior and physics-style simulations, and they speak concretely about rendering performance, mesh optimization, and camera-aware animation logic.”

“Built end-to-end AI products across fintech and healthcare, including a real-time loan risk prediction system and a patient feedback insights platform. Stands out for combining full-stack delivery, production ML/MLOps on AWS, and pragmatic human-in-the-loop safeguards; reported a 22% improvement in prediction accuracy.”

“Built both a fantasy sports analytics product and a privacy-sensitive AI assistant for therapists, showing range across consumer and healthcare use cases. Particularly notable for designing self-hosted, HIPAA-conscious LLM systems with RAG, structured outputs, observability, and human-in-the-loop guardrails for clinical workflows.”

“Backend/cloud engineer who built an AWS serverless IoT system that computes Bluetooth beacon locations from telemetry using heavy scientific Python (NumPy/SciPy/pandas) packaged as Dockerized Lambda, integrated with Java microservices and scheduled batch orchestration. Has deep AWS delivery experience (CI/CD with Code* tools, CloudFormation, cost controls) and has led high-severity incident response including CloudTrail forensics and infrastructure recovery after a compromised-keys crypto-mining attack.”

“Built a senior design project for Webquity LLC: a React/TypeScript Chrome extension and web app helping students with ADHD manage focus, tasks, and productivity across devices. Stands out for combining performance tuning, cross-device sync, accessibility-minded UX research, and polished UI touches like theming, weather-reactive backgrounds, and Lottie-based mascot animations.”

“Full-stack engineer with strong ownership across React, FastAPI, and PostgreSQL who has built real-time collaboration and analytics workflows end-to-end. Particularly compelling for high-growth AI product teams: they’ve also shipped a 0→1 AI-assisted dataset retrieval and summarization capability, balancing MVP speed with scalable architecture and post-launch performance tuning.”

“Frontend-leaning full-stack product engineer with experience in insurance and financial analytics, combining UI design, React/TypeScript implementation, and backend integration. Stands out for shipping data-heavy dashboards, real-time collaborative features, and early generative AI document-analysis workflows using Spring Boot, LangChain, and AWS Bedrock.”