AI Software Engineer | AI Engineer

AI/ML engineer specializing in Agentic AI, LLMs, RAG, and MLOps. I design and deploy cloud‑native AI systems with a focus on reliability, security, and measurable impact.

Professional Summary

AI/ML Engineer with expertise in Agentic AI, Large Language Models, and Retrieval‑Augmented Generation. Skilled in MLOps/LLMOps, model monitoring, evaluation, experiment tracking, and shipping cloud‑native AI systems across AWS, GCP, and Azure with strong focus on Responsible AI and compliance.

Portrait

About Me

I craft pragmatic AI features that feel simple and obvious in hindsight. My approach blends product sense with rigorous engineering, focusing on reliability, performance, and clarity.

Outside of work, I write, mentor, and contribute to open-source tooling around evaluation, vector search, and full‑stack developer experience.

4+ yrs
Experience
20+
Shipped projects
AWS · GCP · Azure
Cloud platforms

Experience

AI Software Engineer · Novada (Novadatech)

May 2025 — Present · Australia
  • Built Agentic AI systems (LLM agents + RAG) automating workflows; +40% efficiency.
  • Optimized GenAI/NLP with LangChain/LlamaIndex; 70% faster deployments, −35% overhead.
  • Implemented LLMOps/MLOps (eval, monitoring, CI/CD); −40% drift, +50% reliability.

AI Engineer & Team Lead · MyMogulMedia

Dec 2024 — Present · United States
  • Applied MLOps with CI/CD for ML; cut deployment time by 50%.
  • Deployed production AI on AWS/GCP/Azure; achieved 99.9% uptime.
  • Improved LLM accuracy (+25%) and training time (−40%) via PEFT/LoRA.

AI Developer & Software Engineer · Fiverr & Upwork

Dec 2020 — Present · Remote
  • Optimized inference with quantization/pruning/distillation; reduced latency and costs.
  • Shipped compliant AI (GDPR/HIPAA) across analytics, recommenders, and automation.
  • Developed REST/GraphQL APIs (FastAPI/Flask) in microservices/serverless stacks.

Selected Projects

Agentic Automation Platform

LLM agents orchestrating multi‑step workflows with tools, memory, and evaluation.

TypeScriptNodeOpenAILangChain

RAG Knowledge Base

Hybrid retrieval with embeddings + BM25, eval dashboards, and observability.

PythonFastAPIFAISSLlamaIndex

LLM Eval Harness

Scenario‑driven evaluation with dataset versioning, quality gates, and reports.

PythonMLFlowWeights & Biases

Contact