Vetted AWS Lambda Professionals

Akashreddy Madduri

Screened

Senior Backend Engineer specializing in real-time data platforms for FinTech and Healthcare

Plano, Texas6y exp

“Backend/data engineer with experience at JPMorgan building near real-time payment risk and fraud scoring pipelines using Python, Spark Structured Streaming, and Delta Lake, emphasizing auditability, security, and data correctness (dedupe/late events) to reduce false positives. Also led a legacy-to-cloud migration of claims/eligibility data at Cogna with parallel runs, phased rollout, and healthcare-specific validation (ICD-CPT mapping).”

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.”

Abhay Ravi Kumar

Screened

Junior Software Engineer specializing in backend, cloud DevOps, and ML/NLP

Bengaluru, India1y exp

“DevOps/data-automation professional with HPE experience who has deployed containerized microservices to AWS EKS and built an end-to-end observability stack (Prometheus/Grafana/CloudWatch via Terraform), reporting zero-downtime deployments and ~40% faster incident response. Also extends Python ETL automation for procurement/operations teams (rules engine, validation, performance tuning) and bridges SAP ERP data into Power BI/Qlik dashboards through close on-site user collaboration.”

Pandari G

Screened

Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems

San Francisco, USA5y exp

“GenAI/LLM engineer with production deployments in both fintech and retail: built an AI-powered mortgage document analysis/automated underwriting pipeline at Fannie Mae (OCR + custom LLM) cutting underwriting review from 3–4 hours to under an hour with privacy-by-design controls. Also helped build Sephora’s GenAI product advisory bot using LangChain-orchestrated RAG (Azure GPT-4, Azure AI Search, MySQL HeatWave vector search), focusing on grounding, evaluation, and compliance-aware architecture choices.”

Sanat Ahuja

Screened

Senior Engineering Manager specializing in platform, data/ML, and identity/access systems

Los Angeles, CA16y exp

“Senior engineering leader from Goodyear’s AndGo startup-like division who scaled the org from 12 to 30+ across pod-based teams and introduced an Architect Guild/ARD governance model. Led a 4-month Europe launch requiring AWS regional infrastructure, GDPR compliance, i18n/l10n, and new EMEA reporting pipelines, and has hands-on depth in API performance, incident response, and GraphQL/Hasura adoption to boost product velocity.”

Sarthak Vinayaka

Screened

Mid-Level Full-Stack Software Engineer specializing in enterprise AI, data pipelines, and scalable APIs

Redwood City, CA3y exp

“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”

Shram Kadia

Screened

Mid-level Software Engineer specializing in backend systems, cloud-native apps, and AI platforms

Santa Clara, CA4y exp

“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”

Mathew Martin

Screened

Mid-level Software Engineer specializing in cloud data platforms and LLM applications

New York, USA4y exp

“LLM/agent builder with experience shipping production LLM features at an early-stage ed-tech mental wellness startup (conversation analysis + structured feedback via FastAPI, OpenAI API, Render, CI/CD). Also built a multi-step dining concierge agent using OpenSearch over Yelp data with fallback query relaxation, and has enterprise data engineering experience at Capgemini migrating databases to Snowflake with robust ETL normalization and data-quality handling.”

Yash Rangucha

Screened

Mid-level Software Engineer specializing in backend microservices and real-time streaming

Illinois, USA4y exp

“Built and owned an end-to-end LLM-powered enterprise retrieval pipeline at ServiceNow, spanning ingestion of structured/semi-structured sources through vector retrieval and real-time API serving. Focused heavily on reliability and quality (multi-stage validation, monitoring, evaluation pipelines) while also driving performance improvements (~35% faster responses) via caching, async processing, and SQL/query optimization.”

“ML/AI engineer with hands-on experience building production healthcare AI systems across predictive modeling and GenAI. They built an end-to-end patient risk prediction platform and a RAG-based clinical summarization feature, combining strong NLP/LLM skills with AWS deployment, monitoring, drift detection, and reusable Python service design to deliver measurable clinical and operational impact.”

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.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“ML/AI engineer with strong production depth across classical ML, MLOps, LLM/RAG, and scalable Python data platforms, with experience at Cisco and Accenture. Stands out for tying technical decisions to measurable business outcomes, including $1.2M annual savings, 40% faster support resolution, and broad internal adoption of shared engineering frameworks.”

Akhil Nakka

Screened

Mid-level Software Developer specializing in FinTech and cloud-native microservices

Remote, USA4y exp

“Full Stack Engineer in fintech (JPMorgan) who owns products end-to-end across React UIs and Spring Boot/Kafka backends, with a strong track record of shipping quickly while maintaining reliability via testing, monitoring, and feature flags. Has hands-on experience scaling microservices for high-volume transactions and debugging production latency using ELK/CloudWatch, plus built an internal Python/Flask automation tool adopted by backend engineers to speed API validation and debugging.”

“AI/ML engineer with production experience across both classical ML and Generative AI, including a real-time banking fraud detection platform at Deloitte and a RAG-based cybersecurity threat analysis feature at Accenture. Stands out for owning systems end-to-end—from feature pipelines and model tuning through deployment, monitoring, retraining, and API/platform reliability—with measurable impact on fraud accuracy, false positives, and SOC analyst efficiency.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“Frontend engineer with Oracle Cerner experience building healthcare operations UIs where accuracy, compliance, and workflow efficiency matter. They’ve owned a sophisticated React-based patient record validation and merge interface and also show solid performance instincts through render optimization, state management, and TypeScript-based API modeling.”

“Full-stack product builder with strong GTM and applied AI experience, including end-to-end ownership of a production lead intelligence platform that combined React/TypeScript, Python services, external data enrichment, and LLM orchestration. Notably reduced SDR research time from 15-20 minutes to under 2 minutes per account and also drove an 8% revenue increase at Finding Pi by building a customer segmentation framework from analysis of 45k+ users.”

“Frontend-focused engineer with experience spanning healthcare, enterprise analytics, and real-time trading products. They have owned React/TypeScript dashboard surfaces end-to-end, including a hospital patient dashboard that cut latency by 50%, and have also shaped backend WebSocket contracts to make real-time systems scale.”

Keerthana Kondabathini

Screened

Senior Full-Stack Engineer specializing in healthcare and financial platforms

5y exp

“Software engineer with experience spanning healthcare platforms at UnitedHealth Group/Optum and B2B SaaS systems at Zoho. Has worked on a startup-like internal product for intelligent medical document processing using microservices on Azure, while also building React dashboards, backend APIs, and Python automation to support clinical and business operations.”

“Full-stack engineer with healthcare and financial services experience who owned an end-to-end appointment scheduling feature at Norton Healthcare, improving scheduling speed and reliability through Angular/TypeScript, SQL Server, Entity Framework Core, Redis caching, and secure APIs. Also brings enterprise modernization experience from IBM and JPMorgan Chase, including microservices migration, CI/CD, and production observability.”

“Full-stack engineer with hands-on ownership of an internal LLM platform, spanning React/NestJS development, PostgreSQL schema design, multi-provider model integrations, and chat/eval pipelines. They also show strong production engineering instincts, having resolved Cognito throttling failures via tracing and led an observability migration to Signoz that materially improved incident diagnosis speed.”

“Front-end/full-stack engineer with hands-on ownership of a sophisticated healthcare digital ID card platform at Centene, spanning React/Next.js UI and Spring Boot BFF architecture. Stands out for combining browser-level debugging, reusable component design, and secure multi-system integration to improve mobile usability, reduce production issues, and support adoption of digital member ID cards.”