Vetted AWS Lambda Professionals

Mos Fard

Screened

Senior Distributed Systems Architect specializing in backend platforms and FinTech

Scottsdale, AZ12y exp

“Full-stack engineer who built an AI-powered visual product discovery feature end to end across web, mobile, backend, and ML integration. Particularly strong in TypeScript-first monorepo architecture, serverless AWS microservices, and productionizing computer vision/LLM pipelines with monitoring, prompt refinement, and human-in-the-loop quality controls.”

“Architecture leader from Disney who managed system, AI, and data architects while staying hands-on in solution design. Has experience building LLM-based video advertising products, designing Kafka-based real-time data architectures, and using MVP/POC approaches to align product and executive stakeholders.”

David Richards

Screened

Staff enterprise architect specializing in governance, automation, and regulated environments

Remote, USA18y exp

“Solutions/Sales Engineering professional who has supported enterprise and upper mid-market B2B SaaS deals across highly regulated industries, then transitioned into enterprise architecture and governance at IQVIA. Stands out for combining AI/RPA solution selling with hands-on architecture and implementation, including a legal AI classification deal that achieved 97% accuracy with zero false positives and an air-gapped UiPath deployment that automated 37% of incoming insurance documents.”

“Full-stack engineer with hands-on ownership of a customer-facing advanced performance metrics experience in the Amazon S3 console, spanning React UI, Python/Node services, Redshift/RDS data access, and AWS IaC/CI-CD with CloudWatch/Route53 operational readiness. Demonstrates strong production instincts around resilience (partial failures, multi-region inconsistencies), progressive rollouts/feature flags, and reliable ETL/integration patterns (idempotency, backfills, reconciliation).”

Ranfei Pang

Screened

Mid-level Software Engineer specializing in AI systems and FinTech

Boston, MA4y exp

“Amazon warehouse-tools engineer with strong full-stack and GenAI systems experience, spanning large-scale provisioning platforms and internal LLM/chatbot products. They’ve owned systems end to end, including React/TypeScript frontends, Java/AWS backend orchestration, and Bedrock-based RAG architectures, with measurable impact on latency, token cost, validation quality, and operational support load.”

“Backend engineer with production experience on an AWS Lambda-based payment service (manually deployed) and hands-on modernization work using parallel-run + diffing to prove parity before cutover. Has practical production troubleshooting experience for batch/pipeline incidents using monitoring/logs and emphasizes idempotent rerunnable jobs for safe recovery; also improved GraphQL performance by refactoring overly broad queries.”

“Data/ML backend engineer with hands-on production experience spanning RAG services (LlamaIndex/OpenAI) and AWS data platforms. Has delivered Terraform-managed AWS architectures (Lambda + ECS Fargate) with secure secrets handling, built Glue-to-Redshift ETL with schema evolution controls, modernized SAS reporting into Python microservices, and achieved major Redshift query speedups (2+ hours to under 15 minutes).”

“Robotics software engineer who has built end-to-end pipelines spanning backend/data processing through model interfaces and hardware integration. Has hands-on ROS2 experience building Python nodes and debugging real-time behavior via profiling, publish-rate tuning, and latency fixes, plus experience standardizing multi-robot communication with QoS adjustments. Uses Gazebo simulation and Docker/CI/CD to catch integration issues early and speed iteration.”

“Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.”

“Robotics software engineer focused on real-time mapping and SLAM in unstructured environments, combining camera-based navigation, GTSAM/iSAM2 pose-graph optimization, and nvBlox ESDF mapping with strong real-time performance on both RTX 4070 and Jetson Orin. Has hands-on ROS 2 + Docker integration experience and has built Isaac Sim plugins/ROS 2 packages to make LIO-SAM work in simulation, plus work on decentralized multi-robot SLAM with heterogeneous LiDARs and edge map building.”

“LLM/agentic systems builder at Verizon who deployed a LangGraph-orchestrated multi-agent ticket-automation platform with RAG (FAISS) to replace brittle rule-based bots. Improved routing correctness by ~30–40%, hit ~300ms latency targets via model routing, and reduced ops workload by ~60% through tight iteration with non-technical stakeholders and strong testing/observability practices.”

“Full stack engineer in the financial/thematic investing domain who built end-to-end applications on AWS. Notably redesigned a slow portfolio analytics workflow by offloading heavy computations to scheduled AWS Lambda jobs and caching results in DynamoDB (TTL), cutting API latency from ~5 seconds to under 300ms while supporting data-heavy daily market processing.”

“Solutions Engineer focused on application and platform security for enterprise cloud-native deployments, advising customers on threat modeling and secure CI/CD practices across AWS and Kubernetes. Has implemented SCA/container scanning and vuln checks in pipelines, tuned thresholds to reduce false positives, and driven outcomes like faster security approvals and smoother production rollouts. Troubleshot high-load Kubernetes failures (OOMKills, registry throttling) and turned fixes into a standard tuning guide.”

“Software engineer with experience at Striim and Amazon who ships end-to-end production systems across UI, backend, ML, and operations. Built a real-time PII detection capability for a streaming data platform by integrating Python ML inference into a Java monolith via gRPC sidecars, achieving ~3M events/hour throughput and ~93% accuracy, and helped drive enterprise adoption (Fiserv, CVS). Also modernized internal Amazon tooling for multi-region scale with modularization and fully automated deployments.”

“Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.”

“Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.”

“Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).”

“Infrastructure/DevOps engineer with primary ownership in enterprise Linux and AWS/Azure production environments (including financial systems). Built secure, repeatable CI/CD pipelines deploying containerized workloads to EKS/ECS and implemented Terraform/CloudFormation IaC with drift detection and rollback practices; lacks direct IBM Power/AIX/PowerHA experience.”

“Data engineer with healthcare (CVS Health) experience who migrated production PySpark workloads to native BigQuery SQL and built a Great Expectations-based validation microservice on GKE (Flask + REST) integrated into Cloud Composer. Has operated high-volume pipelines (~300–400GB/day) and designed external vendor ingestion on AWS (Lambda/Step Functions/Glue) with schema-drift detection, alerting, and backfill-safe controls to protect downstream Snowflake/BigQuery tables.”

“Built and shipped a production enterprise RAG knowledge assistant that returns grounded, cited answers and uses confidence-based fallbacks (clarifying questions/abstention) with monitoring and compliance controls for sensitive data. Implemented end-to-end agent orchestration (function calling, structured JSON, state, retries/rate limits) plus eval/feedback loops, and achieved a reported 30–40% improvement in knowledge-task completion time while reducing hallucinations via retrieval improvements.”

Lavanya Chilakalapudi

Screened

Mid-level Full-Stack Developer specializing in cloud-native web apps and APIs

Tampa, FL5y exp

“Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.”

Velusamy Ramasamy

Screened

Principal Software Architect specializing in cloud platforms, data engineering, and enterprise security

Seattle, WA29y exp

“Engineering leader with experience defining solutions from business requirements through detailed specifications and implementation, emphasizing cost-aware technology selection. Has led architectural changes including adding IBM Cloud alongside AWS for budget reasons and integrating caching/messaging to improve availability and performance, and describes scaling distributed teams via experienced DevOps/QA hires and structured evaluation.”

Akshaya Rajagopalan

Screened

Mid-level Full-Stack Software Engineer specializing in cloud SaaS and accessible web apps

Waterloo, Canada6y exp

“Frontend engineer who leads end-to-end delivery of complex workflow-driven React + TypeScript products on top of Rails/GraphQL backends, with a strong emphasis on typed API contracts, scalable architecture, and automated quality gates. Shipped major features (e.g., inventory reservation at Jobber) using feature-flagged rollouts, close QA collaboration, and performance-focused iteration.”