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Vetted Software Developers in the NYC Metro
Pre-screened and vetted in the NYC Metro.
Staff DevOps Engineer specializing in SRE, Kubernetes, and hybrid cloud platforms
Senior Machine Learning Engineer specializing in large-scale AI systems
Nish Sharma
Executive Engineering Leader specializing in FinTech, Payments, and GenAI transformation
“Fintech product builder focused on AI-native opportunities; recently helped their company operationalize LLMs in customer service and bank ops by creating systems to continuously improve prompts and evaluations. Also drove growth by identifying hooks in a major American retailer distribution channel and integrating into the retailer’s payment flows to become a key part of the user funnel.”
Senior Software Engineer specializing in robotics and automation
Senior Full-Stack Engineer specializing in payments and commerce platforms
Senior Software Engineer specializing in ML, search, and AI-powered backend systems
kartik kanotra
Mid-level Software Developer specializing in cloud data engineering and MLOps
“Software engineer with strong AWS production experience, including an end-to-end historical backfill system exporting ~10PB of CloudWatch logs into a data lake using Step Functions/Kinesis/Lambda/Firehose/Glue. Emphasizes reliability and operability (DynamoDB checkpointing, monitoring dashboards, CI/CD with canary tests) and has also built customer-facing UI work for the Visa Developer Portal using Angular + Spring Boot, plus React/Redux frontend work.”
Mid-level Data Engineer specializing in big data platforms and analytics infrastructure
Ajeeta Asthana
Mid-level Software Engineer specializing in distributed systems and FinTech infrastructure
“Early-career software engineer who owns revenue-critical invoice processing and internal ops tooling end-to-end. Has built TypeScript/React systems backed by MongoDB and Temporal, and designed scalable SQS-based onboarding workflows with FIFO/DLQ monitoring. Notably redesigned an Authzed SpiceDB authorization model, shrinking a 500+ line schema to ~20 lines while meeting sub-100ms p95 latency.”
Senior AI/ML Engineer specializing in conversational AI and full-stack systems
Mid-level Full-Stack Developer specializing in Java Spring Boot microservices
Senior Software Engineer specializing in AI infrastructure and distributed systems
Mid-level Software Engineer specializing in Cloud DevOps and MLOps
Mid-level Full-Stack Software Engineer specializing in cloud-native distributed systems
Mid-Level Software Engineer specializing in FinTech and AWS cloud infrastructure
Mid-Level Full-Stack Java Engineer specializing in cloud-native systems for FinTech and e-commerce
Senior Full-Stack AI/ML Engineer specializing in LLM agents and RAG systems
Mid-Level Software Engineer specializing in full-stack systems and cloud platforms
Mahesh Babu
Mid-level Full-Stack Developer specializing in cloud-native FinTech systems
“Built a lightweight internal JavaScript analytics tracker capturing user interactions (clicks, page views, custom events) with debounced batching, automatic session tracking, and offline event caching via a localStorage-backed append-only queue. Demonstrates practical performance optimization mindset (profiling, memoization/caching) and React performance tuning.”
Jonathan Lazar
Director-level Full-Stack Engineer specializing in web platforms and APIs
“Built Bargain Bricks end-to-end as a solo creator, handling product ideation, design, backend, APIs, website, and native iOS/Android apps. They actively maintain and iterate on the product, which has over 1,000 downloads, and have improved conversion through UI changes that surfaced the best deal above the fold.”
Mahesh Kumar Duvvuri
Senior Full-Stack Software Engineer specializing in microservices and cloud-native systems
“Backend/infra engineer with experience across Nestle, J.P. Morgan, and Capgemini, combining ML systems work (YOLOv8/PyTorch object detection with TFLite edge deployment) with production-grade cloud/Kubernetes operations. Has delivered measurable impact via AWS migrations (25% cost reduction, 99.9% availability), microservice modernization (35% faster processing), and low-latency Kafka streaming for financial dashboards (<100ms) using DLQs and idempotent consumers.”
Aditya Jhaveri
Mid-level Software Engineer specializing in AI, big data, and distributed systems
“Software Developer at NYU (GEMSS) focused on scaling and optimizing a data-heavy asset management web app, including migrating/optimizing data access via Google Sheets API and Firestore. Previously an SDE at Sainapse working on Spring Boot microservices POCs (Kafka, Hadoop at 2B+ record scale). Built an end-to-end Apple Wallet coupon generation/redemption system using PassKit + Google Apps Script with measurable ops impact (40% efficiency gain).”
Meghansh NAGULA
Mid-level Full-Stack Developer specializing in React and enterprise web platforms
“Full-stack engineer with recent JPMorgan experience building GPT-4-powered customer sentiment/feedback analytics products (Next.js 14 App Router + FastAPI + Postgres) and owning them post-launch with CloudWatch/Datadog observability. Also implemented Temporal-based transaction reconciliation workflows with strong reliability patterns (idempotency, retries, DLQ, versioning) and has prior high-scale healthcare dashboard experience at Optum.”
Murali Marupudi
Entry-level Computer Science graduate specializing in software and engineering
“Backend engineer focused on high-throughput Python/Flask systems on AWS, with strong scaling and performance tuning experience (e.g., PostgreSQL join reduced from ~3s to <200ms; background aggregation cut from 10 minutes to <90 seconds with 8x throughput). Has also integrated ML model serving into production APIs (churn prediction) using Celery/Redis batching and AWS Lambda/S3, and designed secure multi-tenant architectures with PostgreSQL schema isolation and row-level security.”