What is a Forward Deployed Engineer?

Forward deployed engineer in a nutshell

• The role: working inside a client organisation to enhance, repair, evaluate, and restore their software, often with AI assistance.

• Tasks within the role: 60% of the work is customer-facing, while 30% involves deploying code and around 10% is internal engineering.

• Salary: Expect to earn around £85,000 a year or over £100,000 a year in London.

• Primary hiring companies: Google, Amazon, Microsoft, Salesforce, Stripe, OpenAI, Palantir, Databricks, and various consultancies

• Demand for the role: 729% increase year-on-year, according to LeadDev data.

• How to get a job in this role: Display a combination of engineering understanding and business acumen.

What is a Forward deployed engineer?

A Forward deployed engineer is a software engineer working inside a customer's environment directly instead of remotely. Their role is to learn more about what the client needs and then provide the code or solutions that fill gaps.

Peter Thiel's Palantir is the company that originally developed the model for intelligence and defence contractors. It's now becoming more widely accepted across various verticals and industries.

Usually, companies run "sprints" inside client firms using teams of Forward deployed engineers. The goal is to generate as much leverage and value in as short a space as possible to keep costs affordable while also providing client companies with the upgraded tools they need to thrive in their industries.

How to become a Forward deployed engineer

The primary source of talent for this role comes from individuals with a software engineering background. These individuals understand foundations and systems and are able to ship commercial-ready production at short notice. They're also able to react to specific bottlenecks or challenges that individual firms may be facing, either based on experience or through understanding the client's unique technical architecture.

Forward deployed engineers sometimes also have a solutions engineering or consulting background. These individuals have engineering depth and instincts about what clients want, making them highly suited to this role. Sometimes you also see forward deployed engineers coming from a data or platform engineering background. This is the shortest hop, which is why it's so common.

If you're looking to become a forward deployed engineer, it's worth remembering that most companies are simply looking for evidence that you can do the job. While formal qualifications and experience are nice, AI skills continue to evolve, and many firms are looking for individuals with cutting-edge knowledge on how to implement solutions quickly.

Why has Forward deployed engineer emerged as an important role for businesses?

Forward deployed engineers emerged as an important role for businesses because of the high failure rate of AI projects. Artificial intelligence holds immense promise for many companies, especially when it comes to improving their workflows, but only a small minority find that it really makes a significant difference to how they operate and their bottom line.

Forward deployed engineers are required to plug gaps in technical skills shortages in many UK companies. While a lot of firms plan to adopt agentic AI within the coming years, right now these systems are not sufficiently advanced to provide the deployments they need to upgrade their businesses and keep pace with industry leaders.

Forward deployed engineers plug this gap by providing the deep human skills needed to implement AI and machine learning systems efficiently while keeping costs reasonable.

The top skills Forward deployed engineers need

• Discovery skills: the ability to communicate findings in non-technical language to client teams

• Commercial judgement: the ability to determine whether a specific implementation will create real value for the client firm

• Technical production engineering insights: skills related to shipping, debugging, and operating real systems under load

• Experience with data work and integrations: APIs, ERPs, messy schemas, and more

• General fluency in AI: understanding of prompting, retrieval, and operating guardrails

• Security and governance: an understanding of how advances in software interact with compliance requirements in specific industry verticals