Forward Deployed Engineer, AI Engineer and Solutions Engineer get mixed up all the time. They need different strengths, and applying for the wrong one wastes months. Here is how they differ. Exact duties vary by company, so always read the job description.

	AI Engineer	Forward Deployed Engineer	Solutions Engineer
Main job	Builds AI features into the company’s own product	Builds custom AI solutions inside one customer’s business	Shows customers how the product solves their problem, mostly before they buy
Works with	Own product and engineering team	The customer’s team, often at their office	The sales team and the customer’s buyers
Coding	Most of the day	About half the day, production code	Demos, proofs of concept, scripts
Customer time	Low	High, after the sale	High, before the sale
Measured on	Features shipped and how well they work	Whether the customer’s problem got solved	Deals won
Travel	Rare	Often	Sometimes

Pick AI Engineer if

• You want to write code most of the day.
• You like going deep on one product for a long time.
• Meetings with customers drain you.

Pick Forward Deployed Engineer if

• You can code well and you also enjoy talking to people.
• You are comfortable with unclear problems and messy data.
• You like seeing your work used the same week, and you are fine with travel.

Pick Solutions Engineer if

• You explain technical things clearly and enjoy presenting.
• You like the business side and working with sales.
• You would choose building a quick demo over maintaining a system for years.

How people move between them

Solutions Engineer is a common first step for people with 1 to 3 years of experience. Most FDE roles listed in India ask for 4 to 6 or more years, so many people reach FDE from a solutions, implementation or backend role. AI engineers who want more customer contact also move into FDE.

For the full FDE path with free resources, read the FDE Roadmap.

This comparison is my own summary of how these roles are usually set up. It is general career information, not a promise of a job.