.png){kind=logo}
Vetted Serverless Architecture Professionals
Pre-screened and vetted.
Senior Data Engineer specializing in cloud data platforms and real-time streaming pipelines
Bryan Holland
Executive AI Product & Controls Engineering Leader specializing in agentic video editing and EV systems
“Startup builder (MagicSeven) who designed and implemented a browser-based, agentic video editor end-to-end, including an AWS event-driven multimodal LLM “indexing” pipeline and an orchestration LLM agent for searching and manipulating footage. Demonstrates deep video file/codec knowledge plus practical production hardening of LLM workflows (format validation, plan/execute, S3-based state for debuggability).”
Sai Haritha Sardena
Mid-level Full-Stack Software Engineer specializing in web, cloud, and AI/ML
“Software engineer with experience at Wipro and Tylmen Tech owning customer-facing onboarding and real-time features end-to-end (React + Spring Boot) and building TypeScript/React apps backed by Node.js microservices (MongoDB, RabbitMQ). Strong in production reliability and fast iteration: feature-flagged rollouts, idempotent APIs/consumers, DLQs, and SLO-driven incident tooling, including an internal QA & release dashboard adopted by engineering and support teams.”
Mounika Nadendla
Senior Data Engineer specializing in cloud data platforms and real-time streaming
“Data engineer focused on building reliable, production-grade data systems end-to-end: batch and real-time pipelines (Airflow/Kafka/Spark) with strong data quality, monitoring/alerting, and incident response. Has experience integrating external API/web data with retries, throttling, and schema-change handling, and serving curated datasets to analytics (Power BI) and backend consumers with performance optimizations like Redis caching.”
Mid-level AI/ML Software Engineer specializing in Generative AI and NLP
Lavrenti DeLavrenti
Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS
“Engineering leader (Director/VP level) who has repeatedly aligned product and engineering through ROI-driven quarterly roadmaps and strong stakeholder communication, including board presentations. Built a parallel cloud team to migrate an on-prem product to the cloud, credited with delivering $9M ARR, and led a Python monolith-to-serverless event-driven microservices transformation. Currently manages distributed teams across Mexico, India, and the US using pod-based structures, clear KPIs, and a supportive accountability culture.”
Emmanuel Olaimolu
Senior Cloud Solutions Architect specializing in AWS and regulated healthcare environments
“Cloud/platform engineer with hands-on ownership of AWS EKS Kubernetes platforms built and upgraded via Terraform, including AWS networking/security, EBS/EFS/S3 storage integration, and reliability validation through CloudWatch plus Prometheus/Grafana. Also has on-prem VMware/vSphere administration experience and day-to-day hybrid on-prem-to-AWS operations (VPN/Direct Connect), with examples of resolving pod instability from an application memory leak and fixing a production connectivity drop via routing/firewall troubleshooting.”
Sravanti Dandu
Mid-level Cloud Engineer specializing in AWS & Azure infrastructure automation
“Backend/platform engineer (American Express) who built a Flask-based orchestration layer to automate infrastructure provisioning and integrated Azure AD/JWT RBAC security. Strong in PostgreSQL/SQLAlchemy performance optimization (70%+ query-time reduction) and scalable async/event-driven architectures, including ML inference pipelines (SageMaker/Azure ML/Hugging Face) and high-throughput job queues (Celery/Redis) with reliability patterns like DLQs and idempotency.”
Devasis Bassu
Executive Technology Leader (CTO) specializing in AI/ML, cloud platforms, and insurance underwriting
“Insurtech R&D leader turned CTO with 25+ years across telecom, DoD, automotive, and commercial insurance. Built patented AI-driven insurance document ingestion (>95% accuracy with 1–3 samples) and led Azure-based backend/service development while managing up to 15 engineers at a commercial P&C MGA that reached a ~$60M book of business (~30 loss ratio) before run-off due to paper issues. Known for hands-on discovery (including field inspections) and rapid MVP delivery, including a risk-inspection iPad app that auto-generated draft reports.”
Tarun Janapati
Mid-Level Full-Stack Engineer specializing in LLM and RAG applications
“LLM/RAG engineer who took a PDF-heavy agent from prototype to production for an Africa-based client, combining Pinecone retrieval with robust PDF parsing (unstructured.io, OCR, structured table extraction). Demonstrates strong production mindset (eval metrics, prompt hardening, security/scalability) and measurable optimization impact (30% efficiency gain, 2x faster responses), and has helped close deals by building security-focused POCs for skeptical IT stakeholders.”
Ajay Varma Tanniru
Mid-level Full-Stack Developer specializing in FinTech web applications
“Backend engineer who built an e-commerce order processing service in Python/Flask with PostgreSQL, focusing on correctness and reliability (idempotency, Redis locks, async payment processing with circuit breakers). Also integrated an ML recommendation system as a separate FastAPI inference service with caching and async embedding updates, reporting ~25% CTR lift, and has experience with multi-tenant isolation using PostgreSQL row-level security.”
Gordon Ng
Mid-Level Software Engineer specializing in AI/ML and distributed systems
“Software engineer with production experience building a serverless monolith and multi-layer video pipeline at easyML, plus hands-on integration of multiple LLM providers (Grok/Claude/OpenAI) into a full-stack app. Interested in robotics via computer vision (OpenCV/OpenMMLab), with a strong real-time systems mindset around SLOs, latency, determinism, and reliability; also has low-level OS experience writing a keyboard device driver.”
Bhargavi Guttikonda
Senior Full-Stack Java Developer specializing in cloud-native microservices
“Backend/platform engineer with production ownership of high-volume transaction analytics and fraud monitoring services built in Java/Spring Boot. Has scaled data processing platforms (including healthcare datasets) and operated Kafka-based event pipelines with schema versioning, deduplication, and replay/backfill workflows, using strong observability via CloudWatch/Grafana and CI/CD with Jenkins.”
Divyansh Agarwal
Junior Machine Learning Engineer specializing in computer vision and LLM applications
“Built and led an autonomous driving software effort for Formula Student, owning the full autonomy stack (perception, planning, control) orchestrated in ROS. Implemented stereo depth + YOLO object detection, RRT/RRT* planning, and a robust SLAM pipeline (Kalman filter, submapping) while leveraging Gazebo simulation and modern deployment tooling (Docker/Kubernetes, AWS, GitHub Actions CI/CD).”
bikramjit ganguly
Staff Full-Stack Engineer specializing in API-driven web platforms and distributed systems
“Highly agent-centric builder who uses Codex daily to generate and manage full application repos, including Next.js CRUD apps, GitHub automation, and AWS lifecycle scripts to avoid long-lived cloud artifacts. They also experiment with multi-agent workflows for parallel development and correctness checking, showing strong practical fluency with emerging AI-native software development patterns.”
Monisha DhanaVijeya
Junior Software Engineer specializing in AI, backend systems, and AWS cloud
“Built and shipped a production multi-agent conversational AI platform (Monitor agent + RAG + 4 additional agents) with enterprise REST APIs, using ChromaDB-grounded WCAG knowledge to keep responses accurate while varying tone via personality modes and conversation memory. Has experience at LinkedIn delivering technical demos and pre-sales guidance to both engineering teams and C-level stakeholders, acting as a translator between sales and technical teams to drive adoption.”
Tuukka Luolamo
Executive Technology Leader (CTO) specializing in AI, cloud, and distributed platforms
“Engineering leader who stays hands-on in high-leverage technical areas (architecture, scalability, reliability) while operating at an executive level. Led StagePilot’s shift from a tightly coupled legacy system to a cloud-native, event-driven real-time platform proven at 1M+ concurrent users, and previously scaled multiple SRE teams at McGraw-Hill with SLOs, on-call, and blameless ops practices.”
Meghanath kethireddy
Mid-level Full-Stack/Backend Engineer specializing in Java microservices and cloud platforms
“PayPal ML/AI practitioner who built and productionized a hybrid recommendation engine (BERT/LLM embeddings + collaborative filtering + XGBoost ranking) on AWS with end-to-end MLOps and orchestration. Addressed real-world issues like cold start and embedding latency (ONNX, clustering, caching, PySpark/Delta Lake) and drove a 27% lift in upsell conversion via A/B testing and stakeholder collaboration with marketing.”
Saumay Killa
Mid-level Full-Stack Engineer specializing in AI SaaS and FinTech
“Built a career platform feature end-to-end that generates tailored resumes and cover letters using a React/TypeScript frontend, Postgres, and AWS Lambda/SQS backend. Strong in event-driven, serverless architecture and pragmatic product iteration, with a quantified 60% improvement in onboarding completion after redesigning the UX with resume parsing and a multi-step flow.”
Chris Colinsky
Executive Technology Leader/CTO specializing in data platforms, AI agents, and e-commerce/payments
“Engineering leader with hands-on coding time who has driven major commerce and data-platform transformations: defined goop’s omnichannel strategy, unified payments to Square, and rebuilt real-time NetSuite inventory flows plus forecasting tools. Currently reorganized engineering into Product/Data/Support teams to hit aggressive seasonal roadmaps, and led a data-lake/medallion ELT refactor feeding embedded analytics (Tinybird) with improved reliability and cost efficiency; also accelerates onboarding via AI coding tools in a serverless, event-driven architecture.”
Rishitha reddy katamareddy
Mid-level Generative AI & Machine Learning Engineer specializing in agentic LLM systems
“Built and deployed a production agentic LLM knowledge assistant that answers complex questions over internal documents, APIs, and databases using a RAG architecture (FAISS/Pinecone) and LangChain/LangGraph orchestration. Emphasizes production-grade reliability and hallucination control through grounding, confidence thresholds, validation, retries/fallbacks, and full observability (logging/metrics/traces) with continuous evaluation and feedback loops.”
Revanth Goli
Senior Data & Backend Engineer specializing in cloud data pipelines and LLM/RAG systems
“Data engineer with end-to-end ownership of large-scale retail and clinical data ingestion/processing on AWS, including real-time streaming and batch pipelines. Delivered measurable outcomes: 20M daily transactions processed, latency cut from 4 hours to 5 minutes, ~70% fewer failures, and 120+ pipelines running at 99.8% reliability with full audit compliance.”
“Unity/gameplay engineer (Playtika) who built a state-machine/ECS-driven slot/bonus engine in a client-server setup, focusing on consistent outcomes under latency and highly engaging reward sequences. Also implemented server-authoritative real-time challenges/contests via an event-driven messaging system (SignalR-like) across iOS/Android/WebGL/UWP, and validates impact through retention/session/engagement analytics.”