Vetted Serverless Architecture Professionals

“Lead engineer/designer behind The Washington Post's internal live-tracker tooling and election coverage interfaces. They combine cloud architecture, frontend/data-viz craftsmanship, and close newsroom stakeholder collaboration to ship real-time, high-traffic journalism products that improved internal efficiency and supported major audience and subscriber outcomes.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in backend systems and real-time analytics

California, USA5y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

“Backend/full-stack engineer with Blue Cross Blue Shield experience building a reactive, event-driven claims processing microservice platform on AWS (ECS, SNS/SQS) with Terraform-based IaC and strong observability (Dynatrace/CloudWatch). Demonstrated measurable production impact (32% less downtime, 24% higher processing efficiency) and deep database performance/migration expertise across MongoDB and Postgres.”

“Full stack Python developer who actively integrates AI coding assistants into day-to-day engineering work, including code generation, debugging, testing, and documentation. Has also coordinated multi-agent workflows across backend, frontend, testing, and code review, showing an applied, productivity-focused approach to AI-enabled software delivery.”

Niharika Bhasin

Screened

Intern Full-Stack Software Engineer specializing in AWS serverless and real-time web apps

New York City, NY0y exp

“New-grad/early-career engineer who led high-stakes modernization of a field-operations platform from Firebase to AWS using an incremental/dual-write strategy, achieving zero downtime and ~30–32% infra cost reduction while improving scalability. Also built and productionized an AI-native code assistant (LangChain + Pinecone RAG) with measurable online metrics and safety guardrails, and has experience working directly with CEO/CTO/CPO and embedded with customer teams to ship enterprise features quickly.”

Brendan Dwyer

Screened

Senior AI/ML Engineer specializing in GenAI and cloud platforms

Colorado Springs, CO10y exp

“ML/AI engineer with hands-on experience turning research-style RAG concepts into production underwriting systems at Prudential Financial. Built an internal document intelligence assistant end-to-end with strong monitoring, safety, and evaluation practices, driving a 38% faster review process and 31% better retrieval accuracy. Also improved platform engineering at VivSoft by standardizing Python-based ML deployment across 60+ models.”

“Candidate approaches AI-assisted coding like a senior developer supervising junior contributors: they define precise technical requirements, enforce code quality and documentation, and review outputs before approval. They also actively lead multi-agent workflows using OpenClaw and a Kanban-style AI project management setup, coordinating both coding and non-technical agents.”

“Entry-level backend engineer currently building AI infrastructure for a legal-tech product, including message APIs between frontend and LLMs and MCP-based integrations to enterprise legal systems. Stands out for owning backend components end-to-end in an ambiguous early-stage environment and for resolving a critical pre-demo bug under intense time pressure.”

Michael Boaz

Screened

Senior Software Developer specializing in cloud-native and event-driven architecture

Atlanta, GA24y exp

“Built and shipped production LLM/agent systems on AWS for internal developer support and IT observability use cases, including a Claude-based support tool grounded in internal documentation and a cost-optimized ServiceNow integration. Stands out for combining agent design, cloud architecture, CI/CD, chaos testing, and observability to make non-deterministic systems reliable and maintainable in production.”

“Pragmatic AI-focused builder who uses tools like ChatGPT and Claude to accelerate development while maintaining strict review, testing, and architectural ownership. Has hands-on experience designing lightweight multi-agent workflows, including a RAG-style system with separate retrieval and response roles, and approaches new AI trends through direct experimentation rather than hype.”