// what i offer

Services

From a first prototype to a system in production — here's how I can help you ship AI that actually works.

AI Agents & Automation

Tool-calling agents that run real workflows — orchestration, guardrails, retries and tracing. From idea to production.

  • Multi-agent orchestration
  • Tool & API integrations
  • Guardrails + retries
  • Tracing & cost caps

GenAI & LLM Apps

Chatbots, copilots and LLM features wired into your product — streaming, function calling, evals.

  • Streaming chat UIs
  • Function / tool calling
  • Prompt + eval harness
  • Provider routing

RAG & Retrieval Systems

Answer from your own documents, not vibes. Chunking, embeddings, reranking and an eval harness that proves it works.

  • Ingestion pipelines
  • Embeddings + vector DB
  • Reranking & citations
  • Retrieval evals

Full-Stack Development

The product around the model — fast APIs, clean interfaces, and the infra that ships it.

  • APIs (FastAPI / Node)
  • React / Astro frontends
  • Auth & databases
  • Dashboards

MLOps & Deployment

Serve models at sane latency and cost — containers, pipelines, monitoring and CI/CD.

  • Containerized serving
  • CI/CD pipelines
  • Monitoring & alerts
  • Autoscaling

Data & ML Engineering

Pipelines, training and fine-tuning for what a prompt can't fix. Clean data in, reliable models out.

  • Data pipelines
  • Training & fine-tuning
  • Feature stores
  • Model evaluation

// specializations

What I build most

RAG Systems AI Agents Multi-Agent Systems Autonomous Agents Voice Agents System Design OpenClaw Agents Hermes Agent

// how i work

From idea to production

01

Discover

We scope the problem, success metrics, data and constraints — so we build the right thing.

02

Design

Architecture, model + retrieval strategy, and an eval plan before a line of production code.

03

Build

Iterative delivery with working demos — accuracy, latency and cost treated as features.

04

Ship

Deploy with monitoring, tracing and docs — plus a clear path to iterate after launch.

// kind words

What people say

Feedback from the teams and founders I've built AI systems with.

Junaid shipped our RAG assistant end-to-end — retrieval quality was the difference between a demo and something our team actually trusts.

AR A. RahmanProduct Lead, SaaS

Rare to find someone who can train the model and build the product around it. Clean APIs, real evals, no hand-waving.

SM S. MalikCTO, Fintech

The agent he built runs unattended every night. Guardrails, retries, tracing — it just works, and when it doesn't we know why.

JC J. ChenHead of Ops

Fast, communicative, and obsessed with latency and cost. Our inference bill dropped while quality went up.

MF M. FarooqFounder, AI Startup

Junaid shipped our RAG assistant end-to-end — retrieval quality was the difference between a demo and something our team actually trusts.

AR A. RahmanProduct Lead, SaaS

Rare to find someone who can train the model and build the product around it. Clean APIs, real evals, no hand-waving.

SM S. MalikCTO, Fintech

The agent he built runs unattended every night. Guardrails, retries, tracing — it just works, and when it doesn't we know why.

JC J. ChenHead of Ops

Fast, communicative, and obsessed with latency and cost. Our inference bill dropped while quality went up.

MF M. FarooqFounder, AI Startup

He treated our messy documents like a first-class problem. Chunking and reranking done right — answers finally cite the source.

LA L. AhmedData Manager

Delivered a full-stack LLM feature in weeks, not months. Streaming, function calling, the whole thing felt production-grade day one.

RI R. IqbalEngineering Manager

Great writing, greater engineering. His breakdowns of what actually works in production saved us weeks of trial and error.

DC D. CostaML Engineer

Reliable partner from prototype to deploy. Owns the system — data pipeline to the button a user clicks.

KY K. YusufVP Engineering

He treated our messy documents like a first-class problem. Chunking and reranking done right — answers finally cite the source.

LA L. AhmedData Manager

Delivered a full-stack LLM feature in weeks, not months. Streaming, function calling, the whole thing felt production-grade day one.

RI R. IqbalEngineering Manager

Great writing, greater engineering. His breakdowns of what actually works in production saved us weeks of trial and error.

DC D. CostaML Engineer

Reliable partner from prototype to deploy. Owns the system — data pipeline to the button a user clicks.

KY K. YusufVP Engineering

// service questions

Before you hire me

How do we start a project?+

A quick call or message to scope the goal, data and constraints — then you get a clear proposal with milestones, timeline and price before any build starts.

What's a typical timeline?+

A working prototype usually lands in 1–2 weeks. Production systems (RAG, agents, full-stack apps) typically take 4–8 weeks depending on scope and integrations.

How does pricing work?+

Fixed-scope gigs run through Fiverr, hourly and long-term contracts through Upwork or direct. Larger builds are split into milestone payments — no surprises.

Can you join an existing team or codebase?+

Yes — remote-first and comfortable plugging into your repo, workflow and review process. I ship in your stack, not around it.

What happens after launch?+

Every delivery includes monitoring hooks, docs and a handover walkthrough — plus an optional support window to iterate once real users hit the system.

Have a project in mind?

Tell me what you're building — I'll tell you the fastest path to shipping it.

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