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Vetted AWS Lambda Professionals
Pre-screened and vetted.
Prathik Goud Makthala
Mid-Level Backend Software Engineer specializing in FinTech and scalable APIs
“Backend/microservices engineer with fintech loan-lifecycle experience operating low-latency (sub-250ms) services in production using Kafka, idempotent transaction design, and Datadog observability. Also built an end-to-end LLM chatbot (React + Flask) with a decoupled model integration layer (FLAN-T5 via Hugging Face) and has experience designing partner-facing REST APIs with OAuth2/JWT and Swagger documentation.”
Uddesh Singh
Mid-level Software Engineer specializing in AI agents and cloud-native microservices
“Built and shipped a production LLM-powered multi-agent system that autonomously generates and publishes YouTube videos end-to-end (trend discovery, script writing, image/caption generation, timestamped video assembly). Emphasizes production readiness with extensive automated testing, Redis/Postgres/TimescaleDB state orchestration, and Prometheus/Grafana monitoring, reporting ~100x faster content production and improved engagement/viewership.”
Vivek Shrivastava
Director-level Technology Leader specializing in data platforms, AI, and media/AdTech transformation
“Technology leader who built a unified platform for Fox live sports production operations starting in 2019, delivering an initial operational system on an ~18-month timeline while simultaneously scaling an in-house engineering team from a service-provider partnership. Led a security architecture for external vendors/partners using a separate Okta instance with zero-trust and passwordless authentication, and drove adoption through strong change management, documentation, and agile execution.”
Vivek Reddy
Mid-level Data Scientist/Data Engineer specializing in ML pipelines, insurance and healthcare analytics
“Built a production assistive-vision iPhone app to help visually impaired users find grocery items, training a custom YOLO detector on 2,000+ self-collected/annotated images and deploying via CoreML with a cloud multimodal LLM for navigation instructions. Brings hands-on AWS serverless + ECS container deployment (CDK/GitHub Actions) and a disciplined approach to AI workflow reliability (state-machine design, offline evals, stress tests, logging/metrics), plus experience communicating model insights to non-technical stakeholders (MOTER Technologies).”
Swagat Adhikary
Junior Software Engineer specializing in LLM agents and FinTech platforms
“AI/LLM engineer with Fidelity Investments experience who built and shipped a production GraphRAG system that augmented prompts with codebase context, improving business analyst efficiency by 15% and saving ~$3.5M annually. Strong in AWS EKS/Kubernetes/Helm and enterprise IAM/OIDC patterns (including cross-account S3 access), with experience mentoring interns and collaborating with non-technical leaders to extend AI pipelines (e.g., adding SQL functionality during MVP).”
Manaswini Gogineni
Junior Software Engineer specializing in cloud infrastructure and full-stack web development
“Full-stack/platform engineer who has owned real-time analytics products end-to-end and built scalable TypeScript/React + Node.js systems using event-driven and microservices architectures (Kafka/RabbitMQ). Also created a widely adopted Go CLI that standardized AWS/Terraform provisioning across multiple teams, cutting environment setup from days to minutes through opinionated defaults, documentation, and cross-org partnerships.”
Gagan Reddy Konani
Mid-level Machine Learning Engineer specializing in LLMs and RAG for healthcare
“AI Engineer (Medtronic) who deployed a production RAG-based clinical assistant grounded in curated biomedical literature (no patient-identifiable data). Deep hands-on experience orchestrating and hardening LLM workflows with LangChain/LangGraph, including stateful agentic flows, rigorous testing, and evaluation; reports a 72% accuracy improvement through retrieval enhancements (query rewriting, multi-query expansion, MMR reranking).”
Nicholas Moore
Senior Full-Stack Engineer specializing in scalable cloud-native systems
“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”
Sakshi Dinesh Deore
Mid-level Software Engineer specializing in AWS, DevOps automation, and data platforms
“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”
Geetha Sri Kasu
Mid-level Software Engineer specializing in Java/Spring Boot, Kafka, and AWS
“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”
Sai Lakshmi Charitaa Andey
Mid-level Business Data Analyst specializing in banking analytics and BI
“Analytics-focused candidate with hands-on experience building SQL reporting tables from messy transactional and master data, plus Python workflows that automate monthly analysis and data checks. They appear strongest in KPI/reporting ownership, metric standardization, and stakeholder alignment, with examples of improving reporting consistency, surfacing issues earlier, and reducing manual reconciliation effort.”
Mustafa Ali
Mid-level Software Engineer specializing in backend systems and AI
“Founding/early backend engineer at ATICA Global who built the company's core hotel property management platform from an empty repo into a production system used by 500+ hotel clients. Combines strong backend architecture with pragmatic product execution, including a dynamic pricing engine that increased partner revenue 17% YoY and an AI-powered sentiment pipeline processing 200K+ reviews/month.”
Akhilesh Padala
Mid-level AI/ML Engineer specializing in Generative AI, NLP, and Computer Vision
“ML/AI engineer with strong end-to-end production ownership across predictive ML and Generative AI use cases. They built a churn prediction platform that cut churn 12% and preserved about $1.2M in annual revenue, and also shipped a RAG-based support assistant that reduced ticket resolution time 30% while improving agent satisfaction and onboarding speed.”
“ML/AI engineer with strong end-to-end production ownership across classical ML and GenAI systems. Built and deployed predictive analytics and RAG-based internal tools on AWS/Kubernetes with measurable impact on accuracy, latency, deployment speed, safety, and user productivity.”
Utkarsh Mittal
Mid-level Software Engineer specializing in backend and distributed systems
“Backend engineer who has owned large-scale systems from design through rollout, including a Dell rearchitecture that unified two regional platforms and delivered major latency gains while scaling the effort from 6 to 150 contributors. Also built an ESG analysis product in an ambiguous startup environment using AWS Lambda, Bedrock/Claude, Flask, and custom data pipelines, showing a blend of distributed systems depth and practical AI integration.”
Abhirup Chakraborty
Junior Software Engineer specializing in backend systems, AI, and search
“Built a complex graph-based search engine to find connections between people and has hands-on experience designing multi-agent coding pipelines that move features through implementation, test generation, testing, and sanity checks. Stands out for treating AI agents like an engineering team, with shared-memory coordination, queue signaling, and completeness-focused guardrails to improve reliability and reduce ambiguity.”
Swetha Pothu Raju
Mid-level Full-Stack Developer specializing in FinTech and payments
“Backend/platform engineer with experience at Fidelity and PayPal, spanning financial systems, payment pipelines, and regulated AI workflows. They’ve owned large-scale deployments end-to-end, including a brokerage platform for 150,000+ accounts, and have hands-on experience integrating OpenAI into internal research tooling with compliance-safe validation and human review.”
Josh Yu
Executive software engineering leader specializing in SaaS platform modernization and AI
“Senior engineering leader with over 20 years of management experience and a hands-on background leading large-scale SaaS, eCommerce, CRM, and customer data platform systems serving millions of users. Stands out for combining deep technical architecture leadership with org-scale people management, including solving multi-tenant SaaS scaling issues, driving self-service product improvements from support patterns, and building governance models for cross-functional delivery.”
Josh Yu
Executive software engineering leader specializing in SaaS platforms and AI transformation
“Senior engineering leader who scaled a global organization from 15 to roughly 100 people and operates comfortably at both executive and hands-on architecture levels. Has led SaaS platform improvements, AI-based compliance workflow automation with LLM observability, and consumer-facing product modernization using analytics-driven UX decisions.”
Vijayagopalan Raveendran
Principal Enterprise Architect specializing in AI, cloud, data, and FinTech transformation
“Solutions/technical consulting professional with enterprise experience supporting major accounts including Costco, MasterCard, Delta Dental of Michigan, and Fannie Mae. Brings a blend of cloud migration, enterprise architecture, security/IAM integration, and business-case development, plus hands-on automation work in Python and GCP to modernize sales-related data processing.”
Bhavneet Kaur
Junior Software Engineer specializing in backend systems and AI/ML
“Backend-leaning full-stack engineer with Amazon production experience on book and author search suggestions, plus hands-on work integrating AI agents with Node.js, Bedrock, and OpenAI Assistants. Also built internal admin tools for safety training, OSHA compliance, and digital badge workflows, showing strength in turning ambiguous operational problems into practical shipped products.”
sushant kumar
Mid-level Full-Stack Engineer specializing in AI and LLM-powered systems
“Shopify full-stack engineer focused on AI/LLM-powered merchant automation products. They have hands-on experience building React/TypeScript and Python/FastAPI systems for long-running agentic workflows, including orchestration, guardrails, observability, and customer-facing trust features, with measurable gains in task completion and latency.”
Ryan Peterson
Senior Full-Stack Engineer specializing in Python web and AI applications
“Backend-heavy full-stack engineer with startup fintech experience who built a real-time lending eligibility service that cut decision time from 12-24 hours to under 5 seconds and lifted conversion by ~15%. Also has B2B SaaS experience automating construction workflows, with strong hands-on work across React/TypeScript, Python/FastAPI, Node.js, Kafka, Redis, and some Go.”
Santhosh padamatinti
Senior Engineering Manager specializing in data platforms, microservices, and enterprise GTM analytics
“Engineering leader (player-coach) recently at Autodesk driving a major sales-motion transformation spanning account hierarchy, commissions/quotas, and downstream financial/sales forecasting impacts. Led cross-functional design with enterprise architects and shipped the end-to-end release, using POCs and Anaplan what-if modeling to validate a risky hierarchy change while coordinating delivery across India/Singapore teams and instituting structured Jira-based tech debt/support tracking and automation (dbt, GitHub Copilot).”