I analyzed 1000 forward deployed engineer jobs: what I learned

It seems every “cool” startup is hiring forward deployed engineers (FDE) these days. But what exactly are these mythical creatures? What are their main responsibilities? How much has demand for them grown? And more importantly, how much are they getting paid?

While Palantir was the one who coined the original title ‘forward deployed engineer’, they unfortunately don’t get to decide what a FDE really is. Neither do thought leaders and LinkedIn influencers (sorry, I don’t make the rules).

So, I decided to analyze 1,000 forward deployed engineer job postings to see how other companies are describing this job, and what the data says about how you can get a forward deployed engineering job.

In this study, you’ll learn the top 10 most mentioned responsibilities, how much job postings has grown this year, the most mentioned skills, the average salary, and more. I’ll also use data (and AI) to settle the debate on whether FDE’s are really different than sales engineers or solution engineers.

Intro: What is a forward deployed engineer?

Before we dive into the data, let’s get clear on what a forward deployed engineer actually is.

A Forward Deployed Engineer is a software engineer who embeds directly with customers to build, deploy, and maintain complex technical systems in production. Think of it as the hybrid of a senior software engineer and a technical consultant, but with way more code and way less PowerPoint.

Here’s what that looks like in practice:

You’re not sitting in your company’s office writing code for an abstract user base.

Instead, you’re on a plane to Chicago on Monday morning because Starbucks just bought your AI platform and needs someone to actually make it work in their environment.

You’ll spend the next 6 weeks embedded with their engineering team, writing production code to integrate your system with their legacy infrastructure, debugging why the AI agent keeps failing, and teaching their team how to maintain it after you leave.

1. The top 10 responsibilities of a Forward Deployed Engineer

What were the the top 10 most common responsibilities mentioned in forward deployed engineer jobs?

Working directly with customers (55%) is the overwhelming #1 responsibility.

Building and deploying AI/ML systems (37%) and deploying to production environments (28%) were #2 and #3, with responsibilities like writing documentation, building prototypes and POCs further down in the list(9%).

Forward deployed engineers spend most of their time on production engineering work (building systems, integrating APIs, troubleshooting issues, optimizing performance), not pre-sales activities, or doing demos.

And notice what’s completely absent from this list: “Hit quota.” “Close deals.” “Generate pipeline.” “Achieve sales targets.” Not a single job mentioned revenue responsibility as a core duty.

2. Demand for Forward Deployed Engineers is up 1165% in 2025

I compared the number of job postings with the job title “forward deployed engineer” from January through October 2025 vs the same period in 2025. Forward deployed engineer jobs exploded by 1,165% year-over-year.

And it’s not slowing down either. In the past 3-4 months, the growth has dramatically accelerated. October 2025 had the highest # of job postings for forward deployed engineers ever.

In 2024, most companies were still figuring out how to use ChatGPT for basic tasks. By 2025, they’re trying to deploy AI agents into production systems.

You can’t just hand that off to a sales engineer who does a nice demo and moves on. You need someone who can actually embed with the customer, write production code, and ensure the AI doesn’t fall apart when it hits real-world complexity.

3. The average FDE salary is $173,816 per year

Forward Deployed Engineer salaries vary, but the median comes in at $173,816 based on jobs that disclosed salary ranges.

70% of FDE jobs mention equity. Only 8% mention OTE (on-target earnings). And exactly 0% are quota-carrying roles.

If this were just a rebranded sales position, you’d see commission structures, OTEs, and quotas everywhere. But you don’t. Forward deployed engineers are compensated like engineers, not salespeople.

Now, here are the top 10 companies paying the most for forward deployed engineers:

AI/ML platforms, data infrastructure companies, and well-funded startups dominate the top spots. And these numbers are just base salary. Most of these companies also offer equity packages worth 0.1% to 1.5% that can be worth hundreds of thousands of dollars.

3b. The average years of experience expected is 5

There’s a perception that customer-facing roles are somehow less prestigious than “pure” engineering. The data though suggests that most FDE engineering jobs require a fair bit of experience.

The experience breakdown among jobs that specify:

• Entry-level (0-2 years): 12% – Rare, mostly at companies building FDE programs
• Mid-level (3-5 years): 60% – The most popular
• Senior (6-8 years): 20% – Common for complex deployments
• Staff+ (9+ years): 8% – For most strategic accounts

FDEs are typically hired at mid-to-senior levels, not junior levels. Companies want engineers who’ve already proven themselves.

Where do FDEs sit organizationally?

Many job postings give us a clue as what teams they’ll be a part of, and who they’ll report to.

• 45% mention FDE as its own dedicated team – Not reporting into sales or customer success
• 38% position as engineering org – “Part of the product engineering team”
• 14% mention GTM/sales team – “Part of the go-to-market organization” (prepare to know how to use Clay 🙂
• 7% mention customer success teams – Post-sales org
• 7% mention solutions/professional services

4. What coding skills do FDE Engineers need?

If you can’t code, you can’t be a Forward Deployed Engineer. Full stop.

Among the top 10 technologies mentioned in forward deployed engineer jobs, Python dominates at 66% of job postings. That’s not surprising.

But here’s what surprised me a bit: TypeScript shows up in 35% of jobs. That’s higher than I expected and tells us something important: forward deployed engineers aren’t just backend infrastructure engineers. They’re building full-stack solutions, often creating custom frontends and dashboards for customers.

The rest of the tech stack reads like a modern engineering role:

• AWS (32%), GCP (22%), Azure (18%) – multi-cloud is the norm, not the exception
• Kubernetes (14%), Docker (12%) – container orchestration is expected

The bottom line? If you’re coming from a pure sales background without coding skills, you’re not getting hired as an FDE. You need to write actual production code. Not scripts. Not glue code. And god forbid, not vibe coding! Real systems that customers depend on.

5. 35% of FDE jobs mention AI agents, 31% require LLM experience

Here’s the breakdown of the most popular AI skills mentioned:

• AI Agents (35%) – building systems that act autonomously
• LLM experience (31%) – working with large language models is now a core skill
• RAG (Retrieval-Augmented Generation) (12%) – this architecture is becoming standard
• OpenAI (8%), Anthropic/Claude (7%) – provider-agnostic is key
• LangChain (4%), LlamaIndex (2%) – orchestration frameworks are emerging

Compare this to traditional ML frameworks:

• PyTorch (6%), TensorFlow (4%) – still relevant but not the focus

What this tells us: FDE roles in 2025 are leaned more on generative AI and agentic systems, not traditional machine learning.

If you want to break into FDE, get comfortable with:

• Building RAG pipelines that don’t hallucinate
• Deploying LLMs that stay within latency budgets
• Creating agentic workflows that fail gracefully
• Making AI systems that enterprises can actually trust

The companies hiring FDEs right now aren’t looking for people who can fine-tune BERT. They want engineers who can deploy Claude or GPT-4 into mission-critical systems and make sure it actually works.

6. Financial services, government, and healthcare are the top customer industries FDEs deploy into

79% of FDE job postings don’t specify what customer industries you’ll be working with. That tells us most FDEs need to be vertical-agnostic – ready to deploy AI systems whether the customer is a bank, a hospital, or a logistics company.

But for the 21% of jobs that DO specify target customers, here were the most popular industries of customers that need forward deployed engineers:

1. Financial Services/Banking (24%) – Document processing AI, risk models, trading systems, compliance automation
   • Examples: Reducto (financial document AI), Galileo (ML observability for financial models), TaxBit (tax compliance for financial institutions), Droit (regulatory compliance for trading)
2. Government/Defense (18%) – Secure AI deployments, air-gapped systems, FedRAMP compliance, classified environments
   • Examples: Lockheed Martin (defense AI systems), Scale AI (DoD AI projects), Obviant (defense/intel solutions), Accenture Federal (government consulting)
3. Healthcare/Life Sciences (17%) – Clinical documentation, medical coding, drug discovery, HIPAA-compliant systems
   • Examples: Anthropic (Claude for healthcare use cases), Commure (hospital software), Foundation Health (healthcare platform), Cohere (healthcare LLM applications)
4. Insurance (17%) – Claims automation, underwriting AI, policy document processing
   • Examples: Federato (commercial insurance AI), Kalepa (underwriting AI), Nirvana Tech (insurance automation), Acrisure (insurance brokerage tech)
5. Energy/Utilities (13%) – Grid management, forecasting models, asset optimization
   • Examples: Atlassian (enterprise software for utilities), Accenture (energy practice), various infrastructure platforms

These are all highly regulated, complex industries where AI deployment is hard. They pay a premium because deployment complexity is the entire value proposition.

7. What soft skills are desired for a forward deployed engineer?

We discussed technical skills, but what are the most popular soft skills mentioned in FDE jobs?

You can be the world’s best AI engineer, but if you can’t sit in a conference room with a non-technical VP and explain why their AI agent keeps failing without making them feel stupid, you won’t succeed as an FDE.

The technical bar is high (hence the $174K average salary). But the differentiator is soft skills. Plenty of engineers can write Python and deploy models. Far fewer can:

• Adapt to a new customer’s industry and tech stack every few months
• Communicate to VPs on why you need to do things a certain way
• Own an entire deployment when things go sideways at 2 AM
• Influence a customer’s engineering team to adopt your architecture recommendations

If you’re a brilliant engineer who hates people, stay in core engineering. If you’re a sales engineer who can’t code, you won’t make it. But if you’re a solid engineer who genuinely enjoys helping customers succeed, FDE is your perfect role.

8. Growth-stage startups have the most forward deployed engineer jobs

How big are companies who usually hire forward deployed engineers?

58% of FDE roles are at companies with 11-200 employees. These are growth-stage startups that have some product-market fit and are trying to scale.

Why? Because FDEs are a scaling strategy for complex products.

Early-stage startups (2-10 people) can’t afford FDEs – the founders are doing the deployments themselves.

Large enterprises (1,000+) have dedicated implementation teams, professional services, and partner networks. They don’t need FDEs for every customer.

But growth-stage startups (11-200 employees)? They’re in the awkward middle:

• Product is too complex for self-serve
• Can’t afford a massive services org yet
• Every customer deployment is still somewhat custom
• Need to move fast and learn from customers
• Strategic accounts require white-glove treatment

That’s where FDEs thrive. You’re engineer #15 at an AI startup, embedding with the first 10 customers to figure out what actually works before productizing it.

9. Forward Deployed Engineers and Sales Engineers are NOT the same role (but there’s ~50% overlap)

Let’s settle this debate once and for all.

I sent 1000+ Sales Engineer job descriptions alongside the 1000+ FDE job descriptions to OpenAI’s API, and asked it to calculate the overlap in responsibilities. How much overlap is there? 50% or so.

They share:

• Customer-facing technical work (95% overlap)
• Product demos (85% overlap)
• POC/pilot management (80% overlap)
• Technical discovery (75% overlap)
• Solution architecture (70% overlap)

But here’s where they differ fundamentally:

The Verdict: These are related but distinct roles.

Sales Engineers are sales-first with technical capability. They’re optimized for sales velocity – get technical validation done, close the deal, move to the next opportunity.

Forward Deployed Engineers are engineering-first with customer skills. They’re optimized for deployment success—get this complex system into production and ensure it keeps working.

Here’s the litmus test:

• If the job has a quota or commission → Sales Engineer (even if they call it FDE)
• If you’re expected to write production code → Forward Deployed Engineer
• If you hand off after the sale → Sales Engineer
• If you’re on-site for 6 weeks fixing production issues → Forward Deployed Engineer

Why the confusion? Because there’s significant overlap (50%) in customer-facing technical work. Both roles bridge product and customer. But their primary objectives and success metrics are fundamentally different.

The rise of FDE as a distinct category reflects the growing complexity of AI/ML/data platforms. These products require deep, hands-on engineering during deployment—work that goes beyond the traditional scope of Sales Engineering.

You can’t demo an AI agent and walk away. Someone needs to actually make it work in production. That’s what FDEs do.

10. Forward Deployed Engineers and Solutions Engineers are not the same job but there’s more overlap here

Now what about solution engineers? I sent 1000+ Solution Engineer job descriptions alongside the 1000+ FDE job descriptions to OpenAI’s API, and asked it to calculate the overlap in responsibilities. How much overlap is there? A bit more: 70% or so.

When Solution Engineers and FDEs have more overlap than Sales Engineers and FDEs. The distinction is subtler but still meaningful.

They share:

• Technical solution design (90% overlap)
• Customer technical advisory (85% overlap)
• Integration architecture (85% overlap)
• Prototype/POC development (80% overlap)
• Production code capability (75% overlap)
• Post-sales involvement (60% overlap – varies widely)

Solution Engineer’s job ends when the customer says “yes, this will work for us”

• You prove the product can solve their problem (demo, POC, technical validation)
• You design how it would fit into their systems
• You answer “can your product do X?” and show them it can
• Once they sign the contract, you move to the next customer
• Someone else does the actual implementation

Forward Deployed Engineer’s job starts when the customer says “yes, now make it work”

• You actually write the code that integrates into their production systems
• You fix bugs at 2am when their deployment breaks
• You’re on-site for weeks/months making sure everything actually runs
• You don’t leave until it’s stable in production and they’re successfully using it
• You’re measured on whether it actually works, not whether they bought it

Litmus tests:

• Do you hand off after the deal closes? → Solution Engineer
• Are you on-site debugging production at 2am? → Forward Deployed Engineer
• Does your manager report to Sales/GTM? → Solution Engineer
• Do you write code that goes into customer production? → Forward Deployed Engineer
• Is your job “done” when the POC succeeds? → Solution Engineer
• Are you still there 3 months after go-live? → Forward Deployed Engineer

Conclusion

While AI will replace many jobs, Forward Deployed Engineering is actually exploding (1,165% growth) because AI agent deployment is hard. Companies need engineers who can embed with customers, write production code, and ensure complex AI systems actually work in the real world.

The role pays like engineering ($174K average) because it requires engineering skills. But the differentiator is customer ability – technical depth + communication skills + adaptability.

If you’re thinking about becoming an FDE:

• Learn Python, and a front-end programming language (66% of jobs require it)
• Get comfortable with AI/ML (35% mention agents, 31% need LLM experience)
• Build customer skills (47% explicitly require customer-facing ability)
• Be ready to travel (68% of roles require it)
• Target growth-stage startups (58% are at 11-200 person companies)

If that sounds terrible, stay in core engineering. If it sounds exciting, welcome to the fastest-growing job in tech 🙂