Forward Deployed Engineer

Ansen Technology; Abu Dhabi; On-site; AED 260,000 - 420,000; Full time

Job summary

Ansen Technology, headquartered in Abu Dhabi, is building a team of Forward Deployed Engineers to work with customers and product teams to design, build, and deploy AI-enabled systems in real environments.

This role sits at the intersection of software engineering, AI product development, solution architecture, and customer delivery, with a focus on scalable production solutions and field insights for the product roadmap.

Qualifications

• Strong software engineering experience in backend, full-stack, data engineering, AI engineering, cloud infra, or enterprise integrations.
• Proven ability to ship working software in real operational environments, not just prototypes.
• Experience with APIs, databases, authentication, deployment workflows, and production debugging.
• Ability to balance speed, reliability, security, and scalability in fast-moving settings.
• Excellent communication skills with both technical and non-technical stakeholders.

Responsibilities

• Work directly with users and technical stakeholders to understand workflows, data sources, pain points, and success criteria.
• Translate ambiguous operational requirements into clear technical designs and deployable solutions.
• Build production-grade applications, APIs, integrations, data workflows, and AI-powered features.
• Develop LLM, RAG, agentic, extraction, classification, and decision-support workflows.
• Deploy and operate solutions using cloud platforms, containers, CI/CD, monitoring, logging, testing, and security controls.
• Debug issues across application, data, model, infrastructure, and integration layers.
• Scale successful pilots into production rollouts across multiple teams or customer environments.
• Identify reusable implementation patterns and convert customer feedback into actionable product requirements and playbooks.

Skills

Software engineering

APIs

Databases

Deployment workflows

Production debugging

Cloud platforms

Tools

Docker

Kubernetes

CI/CD

Terraform

Job description

Ansen is a globally expanding cybersecurity company driven by AI innovation. Headquartered in Abu Dhabi, we deliver advanced security technologies and professional services to government organizations and enterprises across international markets.

Our mission is to build secure, resilient digital systems and protect the peace of the digital world.

Role Overview

We are building a team of Forward Deployed Engineers (FDEs) to work directly with customers, internal stakeholders, and product teams to design, build, deploy, and scale high-impact AI-enabled systems in real operational environments.

This role sits at the intersection of software engineering, AI product development, solution architecture, and customer delivery. You will understand user workflows, rapidly prototype solutions, turn them into reliable production systems, and provide field insights that shape the product roadmap.

This is a team-based role. Individual candidates are not expected to be experts in every area. We are hiring complementary strengths across software engineering, AI/LLM engineering, data systems, cloud infrastructure, enterprise integrations, security, and production deployment.

Key Responsibilities

• Work directly with users and technical stakeholders to understand workflows, data sources, pain points, and success criteria.
• Translate ambiguous operational requirements into clear technical designs and deployable solutions.
• Build production-grade applications, APIs, integrations, data workflows, and AI-powered features.
• Develop LLM, RAG, agentic, extraction, classification, and decision-support workflows.
• Deploy and operate solutions using cloud platforms, containers, CI/CD, monitoring, logging, testing, and security controls.
• Debug issues across application, data, model, infrastructure, and integration layers.
• Scale successful pilots into production rollouts across multiple teams or customer environments.
• Identify reusable implementation patterns and convert customer feedback into actionable product requirements and playbooks.

Required Qualifications

• Strong software engineering experience in at least one major area, such as backend development, full-stack development, data engineering, AI engineering, cloud infrastructure, or enterprise integrations.
• Demonstrated ability to build and ship working software in real operational environments—not only prototypes or demos.
• Practical experience with APIs, databases, authentication, deployment workflows, and production debugging.
• Strong problem-solving ability in ambiguous and fast-moving environments.
• Sound judgment when balancing speed, reliability, security, scalability, and maintainability.
• Excellent communication skills and confidence working directly with both technical and non-technical stakeholders.

Relevant Team Capabilities

Experience in one or more of the following areas is highly valued:

• Software and Product Engineering: Full-stack applications, backend services, APIs, event-driven systems, databases, enterprise integrations, and user-centered workflows.
• AI and LLM Engineering: RAG, AI agents, tool calling, evaluations, prompt regression testing, model monitoring, fine-tuning, inference optimization, and AI red teaming.
• Infrastructure, DevOps, and Security: AWS, Azure, GCP, private cloud, Docker, Kubernetes, Terraform, CI/CD, observability, IAM, audit logging, secrets management, and secure deployment patterns.
• Data and Enterprise Integration: ETL/ELT, streaming, document ingestion, data quality, schema design, and integrations with CRM, ERP, ticketing, SIEM/SOAR, email, document repositories, and internal databases.

Relevant backgrounds may include:

• DevOps or Platform Engineer
• Solutions Architect
• Technical Consultant
• Cybersecurity Engineer
• Enterprise Software Implementation Engineer

Success in the First 3-6 Months

• Deliver working pilots or production features in real customer environments.
• Convert ambiguous requirements into usable technical solutions and repeatable implementation patterns.
• Improve adoption through close user engagement, clear communication, and practical engineering.
• Identify product gaps and provide actionable feedback to the core product roadmap.