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Vetted AWS Professionals
Pre-screened and vetted.
Joseph Herbst
Executive Technology Leader specializing in IoT, PoE building automation, and semiconductors
“Engineering/exec leader (CEO experience) who built a lighting controls and building automation platform from scratch, choosing an Ethernet/PoE and Node.js web-centric architecture that anticipated market shifts and later became an industry pattern. Known for rigorous vendor QA (test-to-failure) and for delivering high-profile deployments (e.g., Black Desert Resort, Resorts World Villa 66) while leading globally distributed engineering teams.”
Junhui Huang
Intern Machine Learning Engineer specializing in LLMs, MLOps, and NLP
“Built and deployed a production LLM-driven Dungeons & Dragons game where the model acts as a dungeon master, adding a structured combat system and a macro-state tree to ensure campaigns converge to a clear ending. Fine-tuned Gemini 2.5 Flash on Vertex AI and deployed on GCP with Kubernetes, using RAG over DnD rules/spells plus multi-agent orchestration (intent-based routing between narrative and combat agents) to reduce hallucinations and improve reliability.”
Alexey Elkin
Junior Full-Stack Software Engineer specializing in cloud analytics and web applications
“LLM/agentic workflow engineer with hands-on experience turning demo-grade LLM analytics into production-ready features by tackling tail latency, observability, and cost/reliability controls. Strong at diagnosing real-time customer incidents via trace-driven debugging across retrieval, tool calls, retries, and prompt/version metadata, and frequently partners with sales as a technical lead to de-risk enterprise pilots through transparent failure-mode walkthroughs.”
Prasannakumar B Vardi
Senior Software Engineer specializing in low-latency ad targeting and distributed backend systems
“Backend/platform engineer who built a high-scale audience segmentation and real-time targeting system using Spark/Glue + S3/Hudi and low-latency API services backed by Redis/relational stores. Demonstrates strong production rigor: Spark performance tuning to eliminate OOM failures, API idempotency/caching to cut p95 latency ~40%, and careful dual-run/feature-flag migrations with reconciliation and rollback runbooks. Experienced implementing layered security with JWT/OAuth, RBAC/ABAC, and database row-level security to prevent privilege escalation.”
Naga Manasa Bandaru
Mid-level Frontend Software Engineer specializing in React, Next.js, and TypeScript
“Product-focused full-stack engineer with FedEx experience building an internal logistics dashboard for near real-time shipment status and performance metrics using Next.js App Router + TypeScript. Strong in production ownership and performance work—uses React Profiler/Chrome DevTools to eliminate expensive re-renders and applies Postgres indexing/query tuning validated via EXPLAIN ANALYZE to improve dashboard responsiveness.”
Jackson Dike
Entry-Level Software Engineer specializing in Machine Learning and AI
“Master’s-level candidate with an academic project portfolio, including ownership of a Python-based video game recommendation system using unsupervised clustering. Has hands-on experience designing the system approach and validating recommendation quality with test cases, plus teaching assistant experience instructing Git/GitHub workflows; limited exposure to Kubernetes, GitOps, and large-scale infrastructure.”
NIDHEESH VELUTHERI
Senior Full-Stack Engineer specializing in modern web applications
“Frontend engineer with insurance-domain experience (AAA Insurance and insurance quoting flows) who has delivered Angular/React/Next.js products end-to-end. Notable for building a complex drag-and-drop email template/code-generation UI and for modernizing React codebases (Redux->Context, lazy loading, memoization) to improve performance and reduce security vulnerabilities, while using feature flags and strong QA automation for fast, controlled releases.”
Yun-Ting Chiou
Junior Full-Stack Software Engineer specializing in TypeScript, React, and Java microservices
“Software engineer with finance-domain experience who built an internal transaction management system end-to-end at Prospect Equities (TypeScript/React Native + Java Spring Boot microservices on AWS), delivering 40% lower query latency and 73% operational efficiency gains. Has also designed Terraform-provisioned, SQS-based distributed systems and scaled workloads to 10,000+ concurrent users, including monolith-to-SOA modernization that cut internal review time by 47%.”
Pranav Chand
Senior AI/ML Engineer specializing in Generative AI and LLM platforms
“Backend engineer focused on multi-tenant enterprise AI personalization and recommendation platforms, combining ML/LLM intent extraction with deterministic policy guardrails for compliance and auditability. Has hands-on AWS experience (ECS/Lambda/DynamoDB/S3) and led a careful DynamoDB single-table migration using dual write/read, canary + feature-flag rollouts, and strong observability/security (JWT/OAuth2, RBAC, Postgres RLS).”
pavan kalyan padala
Mid-level Data Scientist specializing in predictive and generative AI
“AI/ML engineer with production LLM experience in regulated financial services (J.P. Morgan Chase), building a customer response engine to automate first-contact resolution while addressing privacy, bias, compliance, and scale. Strong MLOps/orchestration background (Airflow, Docker/Kubernetes, AWS Step Functions, Azure ML/SageMaker) plus proven ability to integrate with legacy systems and drive stakeholder adoption through dashboards, auditability, and training.”
Sankalp Tiwari
Mid-Level Software Engineer specializing in backend microservices and FinTech data pipelines
“Backend engineer at Goldman Sachs who built LLM-powered reconciliation/reporting services and high-throughput Kafka pipelines (8M+ events/day). Strong in production-grade Python/FastAPI microservices on Kubernetes with GitOps-style CI/CD, plus experience migrating legacy reporting/settlement services onto an internal Kubernetes platform using shadow deployments and gradual cutovers.”
Akshit Modi
Mid-level AI/ML Engineer specializing in healthcare NLP and MLOps
“Healthcare/clinical ML practitioner who built and productionized ClinicalBERT-based pipelines to extract and standardize oncology EHR data, improving downstream model F1 from 0.81 to 0.92 while controlling training cost via LoRA/QLoRA. Experienced orchestrating real-time AWS ETL/ML workflows (Glue, Lambda, SageMaker) and partnering with clinicians using SHAP-based interpretability, contributing to an 18% reduction in readmissions and full adoption.”
Aditya Jaiswal
Intern Software Engineer specializing in cloud, DevOps, and applied AI
“Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.”
Utkarsh Mittal
Intern Data Scientist specializing in computer vision and LLM agents
“Software engineering candidate with hands-on experience building and shipping LLM agents: created a production AI enrichment/coding agent at Covalent Metrology using Apollo.io + OpenAI, and built a Mistral hackathon router that dynamically selects among models to reduce token cost while maintaining quality. Also developed a real-time financial margin analysis agent that emails actionable insights and iterated on reliability issues (e.g., fixing misrouted emails, improving news relevance filtering).”
Bhavyasree Chinthala
Mid-level Data Engineer specializing in cloud data pipelines and real-time streaming
“Data engineer with PNC Bank experience owning high-volume financial transaction pipelines end-to-end (Kafka/REST ingestion through Spark/Glue transformations to Redshift serving) for risk and fraud analytics. Built strong reliability and data quality practices (Great Expectations, reconciliation, Airflow alerting, idempotent retries, incremental/windowed processing), reporting 40% ingestion efficiency gains and ~99.9% data accuracy.”
Srushti Milind Jamsandekar
Mid-Level Software Developer specializing in backend, cloud, and GenAI
“Full-stack engineer with fintech and AI feature experience who shipped an AI-powered project summary module in Next.js (App Router + TypeScript) with secure server-side fetching and route handlers to a FastAPI backend, then owned monitoring and performance fixes in production. Demonstrated measurable UX wins (30% faster dashboard loads) and strong backend fundamentals (Postgres indexing/EXPLAIN ANALYZE, SQS-orchestrated idempotent reconciliation workflows with DLQs and retries).”
Suloni Praveen
Entry-Level Software Engineer specializing in data engineering and ML systems
“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”
Binghan Zhang
Intern Data Analyst specializing in business intelligence and financial analytics
“Analytics candidate with hands-on experience in both fraud and churn use cases, including SQL-based preparation of 6.5M transaction records and reproducible Python modeling workflows. Stands out for combining technical rigor in data quality, feature engineering, and imbalance handling with strong stakeholder alignment, metric definition, and dashboard adoption.”
Atharva Bhide
Entry Software Engineer specializing in AI/ML and multimodal systems
“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”
Prutha Patel
Mid-level Business Analyst specializing in healthcare and data analytics
“Analytics candidate with hands-on experience at BCBS building HIPAA-compliant SQL/Snowflake/Tableau pipelines across fragmented legacy healthcare systems. Stands out for turning a 5-day claims reporting process into a near real-time 10-minute dashboard and for pairing strong data engineering discipline with reproducible Python-based churn modeling that drove measurable retention outcomes.”
Anapuru chetana
Mid-level Business Data Analyst specializing in healthcare analytics
“Analytics-focused candidate with strong SQL, Excel, Python, and Tableau skills who supports payroll-, compensation-, and finance-adjacent processes through rigorous data validation and reconciliation. Stands out for uncovering a duplicate-record mapping issue that exposed roughly $250K in revenue leakage and for building repeatable controls, dashboards, and automated checks to improve reporting accuracy.”
William Rodriguez
Principal iOS Engineer specializing in Swift, SwiftUI, and product-focused mobile platforms
“Product-minded full-stack engineer with deep experience building React/TypeScript + serverless/SQL systems and improving both operational reliability and user activation. They stand out for connecting low-level architecture decisions like idempotency and atomic updates with business outcomes such as reduced support burden and lower 30-day cancellations, while also designing configurable multi-tenant product systems with strong guardrails.”
Kristina Shen
Intern-level Data Scientist and ML Engineer specializing in analytics and AI systems
“Early-career analytics candidate with hands-on experience in SQL/Python data pipelines, Tableau reporting, and marketing engagement analytics across internship and startup settings. Stands out for combining rigorous data quality practices with practical AI system design, including an end-to-end GPT-4 grading capstone that emphasized explainability and human oversight.”
Josiah Aviles
Senior AI/ML Software Engineer specializing in Generative AI and RAG systems
“Built and owned Alight's AI-powered Search Summary feature end-to-end, using a RAG pipeline with OpenSearch and Bedrock, and drove a 20% increase in user feedback scores. Stands out for bringing rigorous production evaluation to LLM systems via live LLM-as-a-judge monitoring, and for experience with advanced agentic architectures, hybrid search, and reranking at scale.”