Vetted AWS Lambda Professionals

“LLM/agentic systems builder who has deployed production solutions for a resource management firm, using an MCP-driven architecture with Neo4j + Elasticsearch and a ChatGPT frontend to generate candidate/company “SmartPacks” and answer entity Q&A. Also built a LangGraph/LangSmith-orchestrated multi-agent workflow that automates data-infra change requests end-to-end (impact analysis, SQL + tests, and PR creation), and delivered a ~60% latency reduction through TTL-based context caching while improving accuracy via a business data dictionary.”

“Data engineer with ~4 years of experience building Python-based data ingestion/processing services and real-time streaming pipelines (Kafka/PubSub + Spark Structured Streaming). Has deployed containerized data applications on Kubernetes with GitLab CI/Jenkins pipelines and applied GitOps to cut deployment time ~40% while reducing config drift. Also supported a legacy on-prem data warehouse/backend migration to GCP using phased migration and parallel validation to meet strict reliability/SLA needs.”

Michael Asadoorian

Screened

Executive CTO specializing in cloud-native SaaS, multi-cloud infrastructure, and AI/ML

Los Angeles, CA28y exp

“Hands-on infrastructure and engineering leader (Director of Global Infrastructure / CTO) who has run double-digit multi-million dollar data center expansion and cloud migration programs and scaled teams rapidly (including offshore/nearshore). Strong AWS and microservices background (Lambda/SQS/SES), with experience balancing deep technical architecture work alongside investor/VC communications and fundraising-related responsibilities.”

Thanuja Mudududla

Screened

Mid-level Software Engineer specializing in full-stack cloud and agentic AI systems

San Jose, CA3y exp

“Backend engineer with hands-on ownership of production systems across maritime tracking, HR tech, and AI-powered document workflows. They combine strong operational instincts with measurable impact—cutting API latency from 10s to 3s, improving query performance by 60%, reducing deployment time by 50%, and driving 70% infrastructure cost savings with serverless design.”

Sreevalli Santhavel

Screened

Director-level AI Product Manager specializing in GenAI, LLMs, and SaaS platforms

Texas, USA12y exp

“Technical Product/Program Manager with architect-level involvement who leads customer-facing product builds from sales discovery and Figma design through engineering estimation, schema decisions, and cloud deployment. Has shipped integrated ecommerce and auction products, including vehicle inventory workflows tied to Salesforce, Stripe, and QuickBooks, and has applied AI/ML to warehouse QA, defect detection, and pricing recommendations.”

“Built and deployed a production, multi-tenant modular agentic AI platform at Easybee AI, using LangChain/LangGraph with Redis-backed durable state to make agents reusable, traceable, and auditable. Emphasizes reliability via strict tool schemas, deterministic controllers, tenant-level policy enforcement, and regression testing derived from real production failures; also delivered AI automation for legal/finance workflows (attorney draw and expense automation) with explainable, deterministic payouts.”

“Built and deployed a production LLM-powered demand and churn forecasting system for an e-commerce client, combining open-source LLMs (LLaMA/Mistral) and Sentence-BERT embeddings to generate business-friendly explanations of forecast drivers. Strong focus on data quality and model trust (validation, baselines, segmented monitoring) and production reliability via Airflow-orchestrated pipelines with readiness checks, retries, and ongoing drift/A-B testing.”

Ashutosh Srivastava

Screened

Senior Engineering Manager specializing in AI platforms and cloud-native backend systems

Sunnyvale, CA11y exp

“Player-coach engineering leader who stayed hands-on (coding/reviews) while leading delivery, including designing an event-driven AI workflow engine with explicit state modeling and robust retries. Built near real-time enterprise analytics for campaign measurement and drove reliability/process improvements (observability, incident runbooks, release management). Introduced lightweight CI/CD and automated testing to cut release time by ~40% while maintaining quality.”