AI Engineer & Solutions Architect — first idea to shipped product.
Currently building LLM applications
Computer Science graduate building AI-powered products, developer tooling and full-stack apps with AI-native workflows. I care about products that ship, memory that persists, and models that behave — currently deep in agentic AI systems, RAG, and multi-agent platforms.
Two competitive AI internships, a published research paper, and 14 builds across multi-agent systems, developer memory, computer vision, voice AI and data intelligence. Open to Founding Engineer, AI Engineering, and AI Solutions Architecture roles.
AI developer tools, multi-agent systems, computer vision, voice AI and data intelligence — each opened to solve a real problem. Scroll: the work moves sideways.
Building an AI-native development platform that orchestrates specialized agents to transform product ideas into structured requirements, system architectures, and actionable development plans with persistent project context and human oversight.
Persistent local memory for AI-assisted dev — every session opens knowing your architecture, decisions and history with signed, offline-verifiable receipts. Zero bytes leave your machine.
“Hey Nimbus.” A wake-word assistant that runs entirely on your machine at $0 — 26 tools across 5 packs, multi-step tool chaining, persistent memory, and measured safety.
Proactive data intelligence engine built to eliminate blind spots — autonomous orchestration engine constantly monitoring data, vectorizing observations, and surfacing anomalies.
Local-first inspector that shows which exact words — yours or a benchmark's — sit inside an AI model's training data. Side-by-side evidence, never a score.
Local-first safety layer for AI coding — tracks AI-generated changes, captures developer intent, and enables instant rollback of unwanted modifications.
Retrieval-Augmented Generation system grounded in documents with semantic vector search, chunking optimization, and defensible citation retrieval.
Streamlined developer navigation and workflow orchestration layer connecting disparate CLI commands, environment switches, and repository actions into a single ergonomic interface.
Computation that refuses false precision — posterior samples show which conclusions the data actually supports, and a verdict gate declines what it can't defend. 172 tests, CI-proven.
Applied AI system simulating a warehouse robot: detects objects using OpenCV, classifies them with a fine-tuned ResNet-18 CNN, and retrieves grounded handling procedures via RAG.
End-to-end personality trait prediction engine using deep NLP pipelines, transformer embeddings (BERT & DistilBERT), and multi-model classification benchmarks.
AI-driven healthcare intake and auto-triage platform for NGOs — automatically triages patient urgency, validates intake data, and organizes volunteer assignment via real-time dashboard.
Modern full-stack task and team workflow platform featuring interactive Kanban boards, project collaboration, priority filtering, and secure role-based access.
The core languages, frameworks and architectural patterns I use to orchestrate autonomous systems and ship production AI products.
Two competitive AI internships and a CS degree — with a published paper and an ongoing Agentic AI program along the way.
Generated human-aligned training signals through strict instruction-following evaluation, correctness checks and quality assessment across text, image and video. Ranking, comparison, prompt writing and defensible decisions to improve model behavior.
Completion certificate ↗Built an end-to-end personality-prediction system with NLP pipelines and multiple ML models, incl. BERT / DistilBERT embeddings — evaluated with standard classification metrics for real-world trade-offs.
“Reinventing Image Generation” — FrameGenX, IJRASET
Open to Founding Engineer, AI Engineering, and AI Solutions Architecture roles — plus research and startup collaboration.
vaishak.v.nair.dev@gmail.com →