Aarish M.

I build production-grade AI applications and full-stack software systems from end to end - from high-level software architecture, data design, and machine learning models to reactive frontends, resilient streaming backends, and automated cloud deployments. My core stack combines TypeScript, React, Next.js, and Node.js on the frontend with Python, FastAPI, PyTorch, LangGraph, PostgreSQL (pgvector), and Redis/Valkey on the backend, deployed across AWS, GCP, and Azure. I take full ownership of the entire product lifecycle: UX/frontend state management, streaming APIs, agent orchestration, background task queues, database architecture, CI/CD, and production operations. Rather than building proof-of-concept scripts or brittle wrappers, I design scalable, secure, and maintainable software ready for real users. What I am Best At ✔️ Full-Stack Product Engineering: Responsive web applications and interactive AI studios using TypeScript, React, Next.js, Node.js, and modern styling libraries. ✔️ Scalable Backend & Real-Time Streaming: High-concurrency backend services in Python (FastAPI, AsyncIO) and Node.js with native WebSockets, NDJSON token streaming, and event-driven architectures. ✔️ Autonomous Agents & Agentic Workflows: Designing reliable multi-agent systems, supervisor/subagent workflows, tool execution, session checkpointing, and self-healing runtimes using LangGraph and LangSmith. ✔️ Machine Learning & Deep Learning: Custom neural network architectures (CNNs, LSTMs, Transformers) in PyTorch and TensorFlow for computer vision, time-series forecasting, and predictive modeling. ✔️ Data Layer, Caching & Search: Database modeling and vector retrieval with PostgreSQL, pgvector, Redis, and Valkey, including hybrid search and tenant-isolated data architectures. ✔️ Cloud Architecture & DevOps: Production deployments, containerization, and infrastructure automation across AWS, GCP, and Azure using Docker, Linux, and automated CI/CD pipelines. ✔️ Security, Governance & Compliance: Enterprise identity enforcement, role-based access control (RBAC), audit-safe logging, CASA verification, and SOC 2 readiness. ✔️ Technical Leadership: System architecture, scope definition, code reviews, and hands-on end-to-end execution. AI, Multi-Agent & Machine Learning I design AI systems engineered for reliability and production use: Agentic Platforms: Supervisor/worker orchestration, persistent execution graphs, tool integration, and deterministic lifecycle states. Deep Learning & Computer Vision: High-accuracy object detection, image classification, and spatial-temporal modeling using PyTorch and OpenCV. Predictive Analytics & Time-Series: Advanced forecasting, tabular machine learning (XGBoost, LightGBM, Scikit-learn), and complex sensor/spatial data pipelines. Document Intelligence & Local LLMs: Automated document parsing, table extraction, and local LLM inference (e.g., Mistral) for unstructured datasets. Cloud, DevOps & Infrastructure I deploy and manage reliable infrastructure across major cloud providers: Cloud Platforms: AWS (ECS, ALB, RDS, S3, CodePipeline, EC2), Google Cloud Platform (GCP), and Azure. Containers & Orchestration: Docker, container registries, managed clusters, and multi-service deployment automation. Database & Cache Management: Automated backups, connection pooling, high-availability PostgreSQL, and Redis/Valkey clusters. Monitoring & CI/CD: GitHub Actions, automated testing, log aggregation, and continuous delivery pipelines. How I Work I am strongest where projects demand both architectural design and hands-on implementation. Whether you need to build an AI product from scratch, connect an autonomous agent runtime to a modern Next.js interface, or scale your backend and cloud infrastructure on AWS/GCP/Azure, I can own the technical roadmap, protect product scope, and deliver production-ready software. 💬 If you're ready to share details about your current projects and active tech stack, we can fine-tune any specific domain focus or adjust the rate/positioning.