Available for new projects · Remote worldwide

    Hire a Remote AI Engineer

    Looking for a remote AI engineer who can take features from prototype to dependable production? I build LLM-powered products, RAG systems, and agentic automations — with the retrieval grounding, evaluation harnesses, and guardrails that separate a demo from something you can safely put in front of users. You work directly with me: one senior engineer, end to end.

    Book a free intro callEmail directly

    What I can help with

    • LLM features and RAG systems with citations and evals
    • AI workflow and agentic automation that removes ops toil
    • Production ML systems with monitoring and retraining
    • Cost and latency optimization for AI features
    • Hallucination mitigation and output guardrails

    Why work with me

    Remote-first, worldwide

    Fully remote delivery with clients across the US, Europe, and Asia — async-friendly and outcome-focused.

    Timezone overlap

    Based in Islamabad (PKT), with working-hours overlap into both US and European mornings/evenings.

    Fixed-price clarity

    Scoped proposals with clear deliverables and timelines — no open-ended retainers required to start.

    Fast, senior delivery

    Direct work with one experienced engineer — no account managers, no hand-offs, working software each sprint.

    Relevant services

    LLM / RAG EngineeringAI Workflow AutomationML Systems & MLOps

    Frequently asked questions

    What does a remote AI engineer do?
    Beyond calling an API, a remote AI engineer designs the retrieval, evaluation, and guardrail systems that make AI features reliable — plus the deployment, monitoring, and cost controls to keep them healthy in production. I deliver all of that remotely, integrated with your existing stack.
    Can you work within our existing AI stack?
    Yes. I target your current cloud and tools (OpenAI, Hugging Face, vector databases, AWS/GCP) rather than forcing a migration, using managed services where they save time and custom infrastructure only where it pays off.
    How do you make AI features production-ready?
    By grounding answers in retrieval, requiring citations, building an evaluation harness that catches regressions before release, and adding monitoring plus guardrails so the system degrades gracefully instead of failing silently.

    Let's talk about your project

    Tell me what you're working on and I'll come back with ideas, a scope, and next steps — usually within 24 hours. Free discovery call, no commitment.

    Start a project[email protected]