Forward Deployed Engineer

7X; Dubai; On-site; AED 180,000 - 240,000; Full time

Job summary

7X is seeking a Forward Deployed Engineer to work with operating companies to turn real-world operational challenges into deployed AI solutions. This hands-on role blends software engineering, AI/LLM development, systems integration and business problem-solving to deliver measurable value.

You will prototype, deploy and hand over production-ready solutions, train users, and track benefits such as cost savings and productivity gains across deployments.

Qualifications

• Bachelor's degree or higher in a relevant field.
• 1–3 years of hands-on experience building and deploying software or AI solutions.
• Experience delivering production-ready AI solutions using LLMs.

Responsibilities

• Work with operating companies to translate operational problems into AI and automation solutions.
• Design, build, test and deploy AI-powered solutions using internal platforms and components.
• Prototype, test with real users and iterate toward production-ready implementations.
• Develop evaluation and testing frameworks to measure AI quality and performance.
• Monitor deployed solutions and troubleshoot integration issues.
• Collaborate with IT, InfoSec, Data & Analytics and business teams on architecture and security.
• Document solutions and prepare technical handover materials.
• Train business users to operate and maintain deployed solutions.
• Identify reusable components to accelerate future deployments and support build-vs-buy analyses.

Skills

Python

LLMs

LLM APIs

Prompt Engineering

RAG

Vector Databases

AI Agents

Workflow Orchestration

API Integration

SQL

Data Pipelines

AI Evaluation

Cloud Deployment

Software Development

Process Automation

Education

Bachelor's degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science, Industrial Engineering or a related discipline

Job description

We are looking for a Forward Deployed Engineer to join our Team and work directly with operating companies across the Group to turn real-world operational challenges into deployed AI solutions.

This is a hands-on engineering role for someone who enjoys working closely with business users, understanding how work is performed, building practical AI solutions and taking them all the way from discovery to production and handover.

The successful candidate will combine software engineering, AI/LLM development, systems integration and business problem-solving to deliver solutions that create measurable operational value.

Key Responsibilities

• Work directly with operating companies to identify operational problems and translate them into practical AI and automation solutions.
• Conduct process discovery, requirements gathering and stakeholder interviews.
• Design, build, test and deploy AI-powered solutions using internal platforms, models and reusable components.
• Develop solutions using Python, LLM APIs, RAG, vector databases, agent frameworks and workflow orchestration.
• Integrate AI solutions with existing operational systems, APIs, data sources and business workflows.
• Rapidly prototype solutions, test them with real users and iterate towards production-ready implementations.
• Develop evaluation and testing frameworks to measure AI solution quality and performance.
• Monitor deployed solutions in production and troubleshoot performance, quality and integration issues.
• Work with Group IT, Information Security, Data & Analytics and business teams to ensure appropriate architecture, security and compliance.
• Document solutions and prepare technical handover materials.
• Train business users and operational owners to use, maintain and extend deployed solutions.
• Track and report measurable benefits from each deployment, including cost savings, productivity improvements and licence displacement.
• Identify reusable components and patterns that can accelerate future AI deployments across the Group.
• Support build-versus-buy assessments by demonstrating the technical feasibility and total cost of internally developed solutions.
• Where required, lead temporary delivery pods or coordinate the work of interns.

Requirements

• Bachelor's degree in Artificial Intelligence, Computer Science, Software Engineering, Data Science, Industrial Engineering or a related discipline.
• 1–3 years of hands-on experience building and deploying software or AI solutions into production.
• Proven experience delivering solutions used by real users beyond proof-of-concept or experimental environments.
• Recent practical experience developing applications using Large Language Models (LLMs) is required.
• Strong experience with Python for application development and/or data-related work.
• Experience working with LLM APIs, prompt engineering and context design.
• Practical knowledge of Retrieval-Augmented Generation (RAG) and vector databases.
• Experience with AI agent frameworks and workflow orchestration.
• Experience with APIs, system integration, SQL and data pipelines.
• Exposure to AI evaluation and testing frameworks.
• Experience with cloud platforms and deploying/managing applications in cloud environments.
• Exposure to lightweight front-end development for internal tools is an advantage.
• Strong process mapping, business analysis and requirements-gathering skills.
• Ability to communicate technical concepts to non-technical stakeholders.
• Experience working directly with clients, business units or operational teams is strongly preferred.
• Exposure to logistics, supply chain or operations-heavy environments is an advantage.

Key Technical Skills

Python | Generative AI | LLMs | LLM APIs | Prompt Engineering | RAG | Vector Databases | AI Agents | Workflow Orchestration | API Integration | SQL | Data Pipelines | AI Evaluation | Cloud Deployment | Software Development | Process Automation

What We Are Looking For

We are looking for an engineer who is comfortable operating at the intersection of technology and business.

You should be able to take an ambiguous operational problem, understand it directly from users, design a technical solution, build it, deploy it into production and ensure that the business can successfully use and maintain it.

Candidates whose experience is limited to academic projects, training or POCs without production deployment experience will not be considered.