Artificial Intelligence Engineer

Full Stack AI Engineer — India (Remote)
Company: AllysAI
Location: Fully remote, based in Jordan
Type: Full-time
Level: Mid-level (3–5 years)
Reports to: Head of AI
Compensation: Competitive fixed salary, benchmarked to experience
About AllysAI
We rebuild enterprise operations as AI-native systems. Production AI shipped like products, powered by AllysOS.
Our clients are large enterprises — pharma, banking, logistics, energy, government — across the Gulf, Europe and Latin America. What we build goes into production and gets used by real operators every day. We are not a demo shop and we do not ship prototypes and call them products.
Headquartered in Abu Dhabi, with offices in New York and Lausanne, and engineering that works wherever the talent is.
The role
"Full stack" here means full stack across the AI system — not React and a database.
You will own a workload end to end: getting the data into shape, building the retrieval and agent logic on top of it, building the evaluation harness that proves it actually works, and shipping it into production where it stays reliable under real client load. Data in at one end, a system a client trusts at the other.
If you have spent the last two years wiring an LLM into a chat box and calling it done, this is not that. We care most about the part that most people skip: knowing whether the thing works, and being able to prove it.
What you'll do
Data. Build the pipelines that get client data — documents, records, exports from systems that were never designed to be read by machines — into a state a model can actually use. Chunking, extraction, cleaning, structuring, indexing.
LLM and agent engineering. Design and build RAG systems, multi-step agents, tool use, and orchestration. Choose the right approach for the problem rather than reaching for the same pattern every time.
Evaluation. Build eval sets and harnesses for the systems you ship. Define what "correct" means for a given client workload, measure it, catch regressions before the client does. This is a first-class part of the job, not an afterthought.
Production. Deploy, monitor, and keep it running — latency, cost per call, failure modes, observability. Own what you ship after it ships.
Iterate on real feedback. Sit close to how clients actually use the system and improve it based on what happens in production, not what happened in your test set.
What we're looking for
3–5 years building software, with meaningful recent time spent on LLM-based systems
Strong Python — this is the working language of the role
Real experience with LLM application engineering: RAG, embeddings and vector search, agent frameworks, tool calling, structured output, prompt engineering as an engineering discipline rather than a guessing game
Evaluation experience — you have built eval sets, run systematic testing on model outputs, and can talk about how you measured quality rather than eyeballed it
Data engineering ability — you can handle messy real-world data end to end without waiting for someone to hand you a clean dataset
Production experience — Docker, CI/CD, cloud (AWS, Azure or GCP), API design. You have shipped things that other people depend on.
Excellent English, written and spoken — you will read client documentation and write for an international team
Based in Jordan and able to work with meaningful overlap with Gulf hours
Independent. Remote means you unblock yourself, communicate clearly in writing, and do not need to be chased.
Nice to have
Fine-tuning, distillation, or model optimisation experience
Enterprise integration work — ERPs, CRMs, internal APIs, legacy systems
Front-end ability (React/Next.js) for building interfaces over what you construct
Arabic
Open-source contributions or work we can look at
What we offer
Fully remote, working from Jordan, on a permanent full-time basis
Competitive fixed salary benchmarked to your experience
Real enterprise problems at scale — not internal tooling, not another chatbot
A small, senior engineering team where your work is visible and your decisions matter
Direct exposure to how AI is actually being deployed inside large organisations in the Gulf and Europe
Room to grow into technical ownership of a product line as we scale

Work arrangement
No