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Currently available for select engagements

Hire LangChain Developer — Agents That Do the Work

When you hire a LangChain developer, you should get agents that complete tasks — not demos that loop forever and burn your API budget. I build LangChain and LlamaIndex agents with strict tool contracts, grounded RAG pipelines, and LangSmith tracing on every run. Each agent ships with guardrails and cost limits.

15+
Years Experience
100+
Projects Delivered
6
Countries Served
$25M+
Revenue Enabled

I'm Omer Muneer Qazi, a Dubai-based Fractional CTO & Solutions Architect with 15+ years of experience and 100+ projects delivered across 6 countries. I build the agents myself and hand over traced, documented systems — need sharper prompts? See hire prompt engineer.

What you get

Agents built as production systems

How we work

From idea to working agent

A structured engagement with no surprises — you’ll always know what’s happening and what’s next.

Why Omer

Why hire through a Fractional CTO

Agent projects fail when the framework does the demo and nobody engineers the tools, evals, or guardrails. As a Fractional CTO, I build agents as production systems — traced, tested, and cost-controlled — the same discipline behind $25M+ in client revenue enabled across 100+ projects.

You get 15+ years of AI engineering across 6 countries and ex-teams at Phaedra Solutions, Integriti, and Nabidios — senior judgment that ships agents which work, without a full-time hire.

FAQ

LangChain developer FAQs

Prompt engineer vs LangChain developer — which do I need?

Need better LLM behavior — tone, accuracy, safety? Hire the prompt engineer. Need agents that use tools, search data, and complete workflows? Hire the LangChain developer. Serious products eventually need both.

How do you stop agents from looping or overspending?

Hard step limits, tool allowlists, and per-run cost budgets kill runaway behavior by design. LangSmith tracing shows exactly where tokens go, so waste gets engineered out.

Can agents work with our internal data?

Yes — RAG pipelines index your documents, wikis, and tickets so agents answer from your knowledge with citations. Data stays in your infrastructure; nothing trains public models.

How long until an agent is in production?

A focused single-task agent ships in 6-8 weeks, including tools, evals, and guardrails. Multi-agent systems take longer — scoping in week one sets the honest timeline.

Will our engineers be able to maintain the agents?

Yes — handover includes traced code, eval suites, and runbooks, plus training on the framework. Your team extends tools and prompts confidently after I step back.

Currently available for select engagements

Hire a LangChain developer who ships

Describe the workflow you want automated and I’ll scope an agent system with honest timelines and cost controls. Dubai-based, working worldwide.