• 🧠 Building production-grade AI systems using LLMs, RAG, and agentic workflows
• 📡 Engineering data platforms & ML pipelines across batch + streaming systems
• ⚙️ Bridging Product Strategy + Distributed Systems + AI Engineering
• ☁️ Deploying scalable AI infrastructure on AWS & Azure
• 🏗️ Experienced across the full lifecycle: data → pipelines → models → APIs → monitoring

I specialize in building AI-powered data products and platform systems designed for real-world scale, reliability, and business impact.

• Production-grade RAG & LLM systems
• AI-powered data platforms
• Distributed data pipelines
• ML infrastructure & deployment systems
• Developer-facing APIs & platform tooling
• AI systems observability & monitoring
• Real-time analytics & decision systems

• I combine Product Thinking + Engineering Execution
• I understand why to build, not just how
• I bridge data engineering + ML + infrastructure
• I build systems that are deployable, observable, and scalable

• 🚀 Built production-grade RAG systems with tool-calling orchestration
• ⚙️ Designed end-to-end ML pipelines (data ingestion → inference APIs)
• 📉 Reduced system complexity via modular AI microservices architecture
• 📡 Worked with real-world data pipelines (batch + streaming)
• 🧪 Applied causal ML for decision systems (policy-level impact)

LLMs RAG Agentic AI LangChain Causal ML (EconML) Evaluation Pipelines

Apache Spark Apache Kafka Apache Flink
ETL / ELT Feature Pipelines Data Modeling

Kubernetes Docker MLflow Terraform
CI/CD (GitHub Actions, Jenkins)

AWS (S3, EKS, SageMaker, Bedrock)
Azure AI (Azure ML, AI Studio)

Python FastAPI Go REST APIs

Prometheus Grafana ELK Stack

🔗 https://github.com/SyedTahaAbbas/causal-ml-for-electricity-access

• Built end-to-end causal ML pipeline
• Estimated treatment effects using EconML
• Performed robustness & sensitivity analysis
• Delivered decision-ready allocation insights

• Advanced RAG architectures (hybrid retrieval, eval systems)
• Real-time AI systems
• AI platform engineering
• Scaling LLM systems in production

If you're building:

• AI products
• Data platforms
• ML infrastructure

→ I’m open to interesting problems and collaborations.