Saad Ul Hassan. Senior Full-Stack AI Engineer.Saad Ul Hassan
Senior Full-Stack AI Engineer
Building production AI products and scalable software
systems.I architect, build and ship production software end to end:
full-stack products, distributed systems, AI agents, RAG workflows and
cloud infrastructure.Product Engineering / AI Systems / Backend & APIs / Cloud
Architecture
Verified engineering outcomes
8+ years
Senior production engineering
~1 hour → minutes
ERP workflow processing
Nearly 99%
Successful transaction processing
capabilities
I own the system, not just a layer.
I work across the product stack, from architecture and backend systems to
AI workflows, cloud infrastructure and production reliability.
01Full-Stack Product Engineering
Architecting and shipping production web and mobile products across frontend, backend, APIs, data and third-party integrations, with strong ownership from requirements through deployment.
Building customer-facing AI capabilities using LLM workflows, agents, RAG, retrieval, tool calling, structured outputs, validation, evaluation, guardrails and graceful failure handling.
LLMs · AI Agents · RAG · Retrieval · Evaluation
03Backend & Distributed Systems
Designing APIs, data layers, asynchronous workflows and distributed services with attention to scalability, idempotency, caching, performance and operational reliability.
Taking systems into production with AWS, containers, CI/CD, observability, performance optimization, security controls and resilient failure handling.
AWS · Docker · Kubernetes · CI/CD · Observability
05Technical Leadership
Providing technical direction through system design, architecture decisions, code reviews, mentoring, incident response, release planning and cross-functional collaboration.
System design · Code review · Mentoring · Incident response
Production AI is a reliability problem.
applied ai in real products
The hard part is not calling a model. It is building the retrieval,
orchestration, validation and failure paths that make AI dependable enough
for customer-facing products.
Agentic workflow
Context → tools → structured result
01Retrieve the right product and domain context
02Orchestrate multi-step model and tool interactions
03Validate structured outputs against expectations
04Retry, fall back and degrade gracefully
05Observe behaviour in production and improve it
Grounded knowledge
RAG and retrieval systems
Documents are chunked and embedded, relevant context is retrieved, and
responses are grounded against that context before reaching the user.
Documents / Retrieval / Context / Response
Designed to improve answer relevance, consistency and trust while
reducing unsupported AI output.
I am a Senior Full-Stack AI Engineer with 8+ years of
experience building production software across SaaS,
marketplaces, construction technology, transportation and
AI-enabled products.
I am strongest at the point where product requirements are
still ambiguous: understanding the business problem, choosing
the architecture, building the system, taking it into
production and keeping it reliable as it evolves.
My work spans TypeScript, React/Next.js, Node/NestJS, Python,
PostgreSQL, AWS and distributed systems, alongside Applied AI
including agents, RAG, retrieval, structured outputs,
evaluation, guardrails and production LLM workflows.
I care about engineering that creates real outcomes:
maintainable architecture, reliable systems, fast products,
secure integrations and teams that can continue moving after
the first release.
selected work
Engineering ownership behind real products.
Production AI, automation and software platforms where I owned meaningful
problems across architecture, implementation, delivery and reliability.
Product names are used where approved. Proprietary source code, internal
data, private topology and unsupported metrics remain excluded.
The wider record of work
👉
experience
A career built through production ownership.
Aug 2025 – Present
Current
Senior Full-Stack AI Engineer
Toptal
Architecture and end-to-end delivery across AI, SaaS, marketplace and automation engagements.
The Agent.Press engagement alone spans its own agent platform, ERP automation for Reis Contracting, AI and Google Business Profile workflows for Local Falcon and an internal Slack assistant for Anaconda, alongside KEYS Community and BookRevs.
Product architecture
AI agents & RAG
Full-stack delivery
Technical leadership
May 2022 – Jul 2025
Senior Full-Stack Software Engineer
Embrace IT
Web and mobile products, microservices and cloud platforms across React, Node.js, Python and AWS.
Full-stack & mobile
Microservices
AWS & Kubernetes
Production operations
Nov 2021 – Apr 2022
Software Engineer / Frontend Lead
Saufik
Projul frontend architecture, leading three React developers and one UX designer.
Improved project performance by 80%.
React architecture
Performance
Team leadership
E2E testing
May 2018 – Oct 2021
Software Engineer
Ineffable Devs
Core VanGo workflows: bookings, payments, user management, authentication and a TypeScript migration.
Reduced initial load time by approximately 30%.
Product delivery
Payments
React
Authentication
Stack, education and recognition
👉
keep in touch
Have a difficult product or engineering problem?
Whether it is a senior engineering role, an ambitious product, or a
production system that needs stronger technical ownership, I am always
open to a good conversation.