Senior AI Engineer

Python Expert

LLM Specialist

Hi, I am Mirza Ali Senior Gen AI Engineer & Architect

With over 10 years of professional experience, I specialize in architecting intelligent, production-grade solutions that bridge the gap between advanced Generative AI and measurable business impact. I have spent nearly a decade transforming complex datasets into autonomous systems that solve real-world problems and drive enterprise value at scale.

My current focus is leading the end-to-end design and deployment of Enterprise LLM applications. I leverage the Azure OpenAI ecosystem, LangChain, and Retrieval-Augmented Generation (RAG) to deliver automated decision support and high-fidelity contextual insights.

Beyond model development, I specialize in LLMOps and Governance. I implement robust evaluation frameworks, automated prompt engineering pipelines, and rigorous monitoring systems to ensure model reliability, safety, and cost-efficiency in production environments.

Technical Expertise

Bridging the gap between cutting-edge research and production-grade AI solutions that drive measurable business impact.

Generative AI

Agentic Workflows: Multi-agent orchestration using LangGraph and AutoGen.
Advanced RAG: Semantic chunking, hybrid search, and multi-stage retrieval pipelines.
Fine-tuning & RLHF: Domain-specific model alignment using PEFT and QLoRA techniques.
Prompt Engineering: Expert-level Chain-of-Thought and ReAct prompting patterns.

Deep Learning

Transformer Architectures: Custom Attention mechanisms and Encoder-Decoder implementation.
NLP & Sequence Models: High-performance RNNs, LSTMs, and GRUs for temporal data.
Core Frameworks: Expert implementation in PyTorch, TensorFlow, and Keras.
Optimization: Advanced Hyperparameter tuning, Gradient Descent, and Regularization.

LLMOps & Governance

Automated Evaluation: Implementing Ragas and DeepEval for hallucination detection.
AI Safety & Guardrails: PII masking, content filtering, and prompt injection protection.
Lifecycle Management: Model versioning and CI/CD via MLflow and Azure.
Resource Optimization: Strategic cost-monitoring and token usage efficiency.

Data Architecture

Big Data Ecosystem: Orchestration with Azure Databricks, Spark, and PySpark.
Medallion Architecture: Implementing Bronze, Silver, and Gold layers for AI readiness.
Vector Infrastructure: Designing semantic search using Pinecone and Azure AI Search.
ETL Orchestration: Pipeline development using Azure Data Factory and Delta Lake.

Professional Certifications

Industry-recognized credentials validating expertise in Cloud Architecture, AI, and Big Data Engineering.

Azure Solutions Architect Expert

Microsoft Certified

Data Engineer Associate

Databricks Certified

Machine Learning Specialist

Microsoft Certified

Azure Administrator Associate

Microsoft Certified

Data Management & Analytics

Microsoft Certified

Querying Data with T-SQL

Microsoft Certified

Big Data Analytics Solutions

Microsoft Certified

Cloud Data Science (Azure ML)

Microsoft Certified

Featured Projects

Production-grade AI systems delivering measurable business impact across enterprise scales.

Enterprise Knowledge Engine

2025

Architected a high-fidelity RAG system for processing 9M+ documents. Implemented semantic chunking and hybrid search to bridge the gap between research and impact.

Azure OpenAI LangChain

Accuracy

95%

Volume

9M+

Autonomous Decision Engine

2026

Developed a multi-agent framework for automated enterprise decision support. Leveraged LangGraph to reduce operational latency by 60%.

LangGraph AutoGen

Efficiency

+60%

Architecture

Multi-Agent

Predictive Analytics Engine

2025

Architected a deep learning forecasting engine using Transformer architectures. Delivered sub-second inference for high-frequency decision support.

PyTorch Databricks

Reliability

99.9%

Latency

<200ms

Real-time Fraud Guard

2024

Developed a low-latency fraud detection engine using Isolation Forests and XGBoost. Processes streaming transaction data via Azure Event Hubs.

XGBoost Event Hubs

Recall

98.2%

Latency

<50ms

Semantic Asset Search

2025

Built a cross-modal retrieval system utilizing CLIP for semantic querying across technical documentation and architectural diagrams.

CLIP Pinecone

Search MRR

0.85

Scale

2M+

Enterprise LLMOps

2026

Designed an automated evaluation pipeline for LLMs monitoring for PII leakage and hallucinations in real-time production environments.

MLflow Guardrails

Safety

99.9%

Savings

40%

TFT Demand Engine

2024

Architected a forecasting engine using Temporal Fusion Transformers (TFT) to reduce global retail stock-outs.

PyTorch Databricks

MAPE

<5%

Impact

$2M

Clinical Insight RAG

2025

Developed a RAG system for medical researchers. Implemented semantic chunking and re-ranking for clinical accuracy.

LlamaIndex HIPAA-ready

Accuracy

96%

Speed

500p/m

Propensity to Pay Model

2023

Engineered a LightGBM classification model to prioritize financial recovery. Optimized feature selection using SHAP values for explainability.

LightGBM Scikit-Learn

ROC-AUC

0.89

Lift

+22%

Deep Intent Evolution

2024

Implemented a Deep Interest Evolution Network (DIEN) to model complex user behavior sequences. Leveraged Attention mechanisms for high-value conversion prediction.

TensorFlow Deep Learning

Precision

91%

Impact

+15%

Career Journey

A decade of engineering evolution—from building data foundations to architecting autonomous intelligence.

Architect Phase 2020-Present

Senior Gen AI Engineer / Architect

Tech Mahindra, Australia

Leading Enterprise GenAI strategy with LangGraph & Multi-agent orchestration.
Delivering $10M+ business impact through high-fidelity RAG systems.

2019-2020 Engineering Phase