HaseebKhizarLet's talk

Expertise

Software architecture, applied AI, and product engineering. Kept connected.

I help teams make the technical call, build the right amount, and leave behind a system people can understand and run.

AI that does a real job in the product.

AI systems

I design agentic workflows, retrieval systems, document intelligence, and evaluation loops around a clear user or operator decision, not around an AI demo.

  • LLM applications
  • Agents and orchestration
  • RAG and knowledge systems
  • Evaluation and guardrails

Cloud architecture the team can understand and change.

Cloud architecture

I shape service boundaries, data flows, infrastructure, observability, and delivery practices so the product can grow without making every change risky.

  • AWS platforms
  • Distributed systems
  • APIs and integrations
  • Reliability and observability

Product thinking and engineering in the same room.

Product engineering

I bring product judgment and hands-on engineering together to clarify the problem, choose the right scope, and ship a coherent first version that can evolve.

  • Product strategy
  • Full-stack delivery
  • Technical direction
  • Engineering leadership
A modular systems campus with distinct service pavilions, visible data paths, an isolated maintenance courtyard, and an observability tower.

If the boundaries are clear, the team can move.

I use architecture to clarify what each part owns, how data moves, where failure is handled, and where the next change should begin.

Technical range

The tools change. The judgment carries forward.

System architecture

Service boundaries, APIs, data flow, resilience

AWS platforms

Cloud primitives, containers, delivery, observability

Node.js

Product services, integrations, real-time workflows

Java

Long-lived services and enterprise systems

Python

Automation, data work, and applied AI systems

Applied AI

LLMs, retrieval, agents, evaluation, document intelligence

Product engineering

React, PostgreSQL, Salesforce, cross-functional delivery

Engineering leadership

Teams, technical direction, execution, product judgment

How the work moves

Four practical moves from uncertainty to production.

Frame

Clarify the outcome, users, constraints, and highest-risk assumptions.

Architect

Choose boundaries, data flows, and technical decisions that fit the actual stage.

Build

Ship the smallest coherent system with observability and feedback built in.

Evolve

Learn from production, remove friction, and strengthen what the product proves it needs.

Discuss a system