Forward Deployed AI Engineer

SussexDigital; Crawley; Hybrid; GBP 90,000 - 150,000; Full time

Job summary

Viridien / CGG is seeking a Forward Deployed AI Engineer to design and operationalise agentic AI systems in production across cloud, on-premises, hybrid and restricted environments.

The role focuses on secure, scalable architectures, integrations, deployment and operational support in Crawley with a hybrid working pattern and full-time arrangements.

Qualifications

• Degree in CS/AI or equivalent practical experience.
• Strong Python programming and production software-engineering skills.
• Experience developing, integrating and operating enterprise AI applications.

Responsibilities

• Design production architectures for agentic AI, LLM and vision-language apps.
• Adapt agent workflows, models, tools and retrieval systems for production.
• Integrate AI systems with enterprise APIs, databases and data platforms.
• Develop reusable connectors, APIs and Model Context Protocol tools.
• Build automated CI/CD, testing, configuration management and deployment workflows.
• Implement authentication, access control, secrets management, security and auditability.
• Establish monitoring, logging, tracing, alerting and evaluation for models.
• Optimize systems for reliability, latency, throughput, scalability and cost.

Skills

Python

Production software engineering

APIs & data pipelines

Security & authentication

Monitoring & logging

Troubleshooting

CI/CD

Docker

Cloud / on-prem deployments

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

CI/CD pipelines

Job description

Viridien / CGG

Crawley

Viridien / CGG is recruiting for the role of Forward Deployed AI Engineer. This role adapts and operationalises agentic AI systems in production across cloud, on-premises, hybrid and restricted environments. It focuses on building secure, scalable and reliable solutions, with work spanning architectures, integrations, deployment and operational support.

Role details

• Location: Crawley
• Working pattern: Hybrid
• Job type: Full time

What you'll do

• Design and implement production architectures for agentic AI, LLM and vision-language applications.
• Adapt agent workflows, models, tools, retrieval systems and configurations for production use.
• Integrate AI systems with enterprise APIs, databases, applications and data platforms.
• Develop reusable connectors, APIs and Model Context Protocol tools.
• Build automated CI/CD, testing, configuration management and deployment workflows.
• Implement authentication, access control, secrets management, security and auditability.
• Establish monitoring, logging, tracing, alerting and evaluation for models, agents and tools.
• Optimise systems for reliability, latency, throughput, scalability and infrastructure cost.

What they're looking for

• A degree in computer science, software engineering, artificial intelligence, engineering or a related discipline, or equivalent practical experience.
• Strong Python programming and production software-engineering skills.
• Experience developing, integrating and operating enterprise software or AI applications.
• Practical understanding of LLMs, agentic AI, tool calling and retrieval-augmented generation.
• Experience building APIs, services and data pipelines, with Docker and cloud or on-premises deployments.
• Understanding of authentication, networking, access control and enterprise security.
• Experience implementing monitoring, logging and operational support for production systems.
• Strong troubleshooting skills across application, AI, infrastructure, network and data layers.

Additional role information

• The role also mentions Docker and cloud or on-premises deployments among the required experience.
• Desirable experience includes deploying agentic or generative AI applications in production.
• Desirable experience includes Azure, AWS or Google Cloud, Kubernetes, Helm, Terraform and CI/CD technologies.
• The advert states an interest in applying AI to scientific, engineering, energy or geoscience workflows.