Artificial Intelligence Engineer - Emiratisation

Albatha Group

Dubai

Sur place

AED 240 000 - 380 000

Plein temps

Il y a 2 jours
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Résumé du poste

Albatha Group is seeking a Forward Deployed Engineer to embed with client teams and turn AI demos into production systems. You will own the full arc from problem understanding to deployment, building LLM-powered solutions and integrating with customer data and tools.

Ideal candidates ship production AI, design reusable components, and communicate trade-offs to both technical and executive audiences. Travel to customer sites may be required.

Qualifications

  • 4+ years of software engineering experience with Python and TypeScript.
  • Hands-on experience shipping LLM applications to production: prompt design, RAG, agents, tool use, structured outputs.

Responsabilités

  • Embed with customer teams to understand workflows, data, and constraints, and identify where AI can deliver measurable value.
  • Scope and prioritize use cases with technical and business stakeholders, turning ambiguous problems into clear delivery plans.
  • Design and build production AI solutions: LLM-based agents, retrieval-augmented generation (RAG), tool/function calling, document processing, and workflow automation.
  • Integrate with customer systems such as data warehouses, CRMs, ticketing tools, internal APIs, and legacy software.
  • Build evaluation harnesses and monitoring so quality, latency, cost, and safety are measured, not guessed.
  • Deploy and operate solutions in customer environments, including cloud, VPC, and on-prem setups with security and compliance requirements.
  • Iterate with end users after launch, tuning prompts, retrieval, models, and UX based on real usage.
  • Turn repeated customer needs into reusable components, and bring product and research teams concrete feedback from the field.
  • Present results, trade-offs, and roadmaps to executives and engineers alike.

Connaissances

Python
TypeScript
LLM applications
API integration
Cloud infrastructure

Outils

AWS
GCP
Azure
CI/CD

Description du poste

As a Forward Deployed Engineer (FDE) at Albatha Group, you embed with our internal customers to turn AI from a promising demo into a production system that moves their business. You will own the full arc: understand the customer's problem, design and build LLM-powered solutions, deploy them into messy real-world environments, and feed what you learn back into our product.

This role suits engineers who like being close to the problem, can write production-grade code, and are equally comfortable in a whiteboard session with a C level and a debugging session with a data team.

What you'll do
  • Embed with customer teams to understand their workflows, data, and constraints, and identify where AI can deliver measurable value.
  • Scope and prioritize use cases with technical and business stakeholders, turning ambiguous problems into clear delivery plans.
  • Design and build production AI solutions: LLM-based agents, retrieval-augmented generation (RAG), tool/function calling, document processing, and workflow automation.
  • Integrate with customer systems such as data warehouses, CRMs, ticketing tools, internal APIs, and legacy software.
  • Build evaluation harnesses and monitoring so quality, latency, cost, and safety are measured, not guessed.
  • Deploy and operate solutions in customer environments, including cloud, VPC, and on-prem setups with security and compliance requirements.
  • Iterate with end users after launch, tuning prompts, retrieval, models, and UX based on real usage.
  • Turn repeated customer needs into reusable components, and bring product and research teams concrete feedback from the field.
  • Present results, trade-offs, and roadmaps to executives and engineers alike.
What you'll bring
  • 4+ years of software engineering experience, with strong Python and working fluency in TypeScript or a similar language.
  • Hands-on experience shipping LLM applications to production: prompt design, RAG, agents, tool use, structured outputs, and fine-tuning where it fits.
  • Practical knowledge of evaluating AI systems, including building test sets, using LLM-as-judge methods, and tracking regressions.
  • Experience with vector search, embeddings, and data pipelines, plus solid SQL and API integration skills.
  • Comfort with cloud infrastructure (AWS, GCP, or Azure), containers, and CI/CD.
  • Clear communication with both technical and non-technical audiences, including the ability to run workshops and explain trade-offs plainly.
  • A bias for ownership: you take a problem from vague request to deployed, working solution.
  • Willingness to travel to customer sites as needed (see logistics below).
Nice to have
  • Prior experience in a forward deployed, solutions engineering, consulting, or startup founding role.
  • Experience with agent frameworks, Model Context Protocol (MCP), or multi-agent orchestration.
  • Background in a regulated industry such as finance, healthcare, or government, including security reviews and data governance.
  • Familiarity with model serving, inference optimization, or open-weight model deployment.
  • Experience with front-end work to build quick internal tools and prototypes for customers.
  • Contributions to open-source AI tooling or published technical writing.
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