System Initialized

Hi, I'm
Aryaman

AI SystemsProduct Engineer

Specializing in deterministic hybrid AI systems, Model Context Protocol (MCP) implementations, and event-driven automation architectures.

01. About Me

I am an AI Systems and Product Engineer specializing in the design, deployment, and optimization of production-ready AI applications and scalable cloud backends.

I combine an institutional foundation in computer science with proven entrepreneurial execution. Currently, as the Co-Founder & Lead Engineer of CONSULTAX and former founder of DIGIMARKETRIX, I build deterministic hybrid AI systems, MCP implementations, and event-driven automation architectures to solve real-world enterprise problems.

My long-term mission is to build AI products that drive actionable impact while contributing meaningful open-source software (like OSEF and JARVIS AI) to the developer community.

> let aryaman = new Developer();> aryaman.skills.push("Agentic AI", "Cloud Native", "Autonomous Systems");█

02. Experience

Co-Founder & Lead Engineer

@ CONSULTAX
Jan 2026 – Present

Architected an enterprise AI tax platform utilizing a decoupled serverless backend. Engineered high-accuracy RAG pipelines and designed stateful AI workflows to safely orchestrate Indian ITR and GST filing schemas.

Software Developer

@ CLOUDWAYZ SOLUTIONS
Jan 2026 – Jul 2026

Engineered responsive front-end components seamlessly integrated with modular backend architectures. Designed and deployed automated, AI-driven workflow solutions to programmatically drive multi-channel marketing infrastructure.

Founder & Systems Engineer

@ DIGIMARKETRIX
Jan 2024 – Dec 2025

Designed and deployed an automated, event-driven social media orchestration engine using AWS Lambda, Amazon EventBridge, and Amazon S3. Engineered an intelligent lead generation and contextual personalization outbound engine.

Online Volunteer (AI Systems Automation)

@ UNITED NATIONS VOLUNTEERS
Jan 2026 – May 2026

Developed Python-based automation scripts and robust prompt engineering matrices to optimize internal systems processing and accelerate global collaboration reporting workflows.

03. Skills Map

AI Expertise

Agentic AIOpenAI Agents SDKRAGMCPPrompt EngineeringMachine Learning

Programming

PythonTypeScriptJavaScriptJavaC++C

Web & Backend

Next.jsReactDjangoNode.jsPostgresMySQLSupabaseRedis

Cloud & DevOps

DockerKubernetesAWSLinuxGitGitHub Actions

04. Selected Projects

OSEF

Open Source Engineering Framework mapping multi-language codebases into queryable semantic context structures for autonomous agents. Features deterministic evaluation runtimes and policy compliance engines.

PythonTypeScriptPolicy EngineAgentic AI
V

VERIFEX

Enterprise AI auditing platform using cloud storage data pipelines integrated into a secured PostgreSQL database. Developed the UCARE architecture combining deterministic schema inversion with an NVIDIA 70B LLM fallback.

PostgreSQLSupabaseNVIDIA 70B LLMCloud Data Pipelines
J

JARVIS AI

High-performance AI productivity platform implementing the Model Context Protocol (MCP) for uniform context synchronization. Features a provider-agnostic LLM integration layer with stateful agent orchestrators.

MCPLLM OrchestratorsContext Synchronization
A

ADHD.AI

Real-time gamified productivity platform optimized for cognitive diversity with low-latency client-side state synchronization.

React NativeNode.jsExpressFirebase
A

AI for Everyone and Everything

Author of a comprehensive handbook demystifying artificial intelligence, exploring practical applications, generative AI, and automation for all skill levels.

AuthorAI/MLEducation
P

Post Quantum Cryptography Research

Author of a research paper proposing a 12-Key Dynamic Encryption Model against quantum attacks.

CryptographyResearchSecurity

05. Client Projects

Project Dynamo

AI Engineering Fellow (Remote Contractor)

Agency: Aryaman Intelligence

18.5 hours
p99 < 50ms Latency

About the Project

Project Dynamo is a cutting-edge initiative within the Handshake AI Fellowship, designed to evaluate, benchmark, and stress-test the next generation of advanced AI coding agents and Large Language Models (LLMs). The project consists of highly complex, adversarial software engineering puzzles—often referred to as "boss-fight" tasks. These environments are seeded with intentional red herrings, hidden constraints, and deep infrastructural complexity designed to make standard AI agents fail, allowing researchers to map their weaknesses and improve their reasoning capabilities.

Debugging & Repair

Complex concurrency, resource starvation, and backpressure mechanisms.

Distributed Systems

Log parsing, clock-sync anomalies, and distributed tracing.

My Contributions

I successfully solved and validated two of the most demanding adversarial infrastructure tracks within Project Dynamo. My work proved the root causes of these simulated production outages and established the benchmark solutions that future AI agents will be tested against.

1. API Gateway Concurrency & Resource Optimization
Ref: dynamo-c2c8e90-debugging-and-repair

The Challenge: An asynchronous API gateway and caching layer was silently degrading and hanging under sustained load. The codebase was riddled with intentional decoys, such as a synchronous thread pool and a global lock that falsely resembled a classic lock-ordering deadlock.

The Solution: I diagnosed a severe concurrency bug related to partial failure cancellation and dynamic backpressure. When backend requests timed out (CancelledError), the cancellation handler failed to properly notify the asyncio Condition variables, leaving phantom connections checked out. I engineered a robust asynchronous context manager for connection checkout that guaranteed state reconciliation and proper load-shedding during pool starvation.

The Result: The updated gateway passed a strict, deterministic load test, processing high-throughput simulated traffic with a strict p99 latency ceiling (50ms) and zero leaked connections.
2. Distributed Tracing & Causal Timeline Reconstruction
Ref: dynamo-108dc99-file-and-media-operations

The Challenge: Debugging a mock distributed system (Gateway, Auth, Database) where all internal clocks were severely skewed. The log data was intentionally chaotic, featuring heterogeneous timestamp formats and idiosyncratic trace_id serializations.

The Solution: I built a custom, highly resilient parsing pipeline to normalize the raw telemetry data. By identifying symmetric RPC round-trips, I mathematically calculated the exact, constant integer millisecond clock offsets for each microservice. I patched a deliberate anomaly where the Database service logged timestamps exactly 1337ms in the future.

The Result: I generated a mathematically flawless, unified causal JSON timeline for the system's most critical traces, perfectly aligning the infrastructure's observability data and allowing for deterministic root-cause analysis.

05. Ventures

Digimarketrix

Founder & Digital Strategist

Building digital systems where Marketing and AI Strategy intersect. Digimarketrix isn't just an agency—it's an analytics-driven growth engine leveraging affiliate marketing, automated social media strategies, and deep data insights to scale modern brands.

Discuss Strategy

Consultax

Founder & Developer

An AI-powered tax consultancy platform simplifying financial workflows through intelligent automation. Consultax features a highly scalable backend, intelligent consultant discovery, and an AI Tax Assistant designed to guide users seamlessly.

Visit Platform

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