$134,500–$265,100
From implementation and data engineering to FDE
753 of 2,359 postings ask for implementation and data engineering · 341 companies · 577 state pay: median $190,000, half $160,000–$216,000
Postings read on
Published · Updated
Stated in the posting
552 of these 753 postings state a minimum number of years, most often 3–5 years.
Share of those 552.
11.2%48.4%33.7%
- 0–2 years62 postings · 11.2%
- 3–5 years267 postings · 48.4%
- 6–9 years186 postings · 33.7%
- 10+ years37 postings · 6.7%
201 postings state no number.
The minimum number of years each posting states. A posting that gives no number is not a posting that wants none.
Our reading of the posting
408 of these 753 postings build what the customer runs.
54.2%18.1%11.7%11.0%
- Builds what the customer runs408 postings · 54.2%
- Integrates and configures it136 postings · 18.1%
- Plans what the customer deploys first88 postings · 11.7%
- Builds for teams inside the company83 postings · 11.0%
- Leads the deployment team32 postings · 4.2%
- Proves it works before the sale4 postings · 0.5%
- Keeps customers running after launch2 postings · 0.3%
What an employer asks you to arrive with and what the job turns out to be are two readings of one posting, and they disagree constantly. The guide below is about the first. This bar is the second.
Pay not posted
Pay not posted
Senior Forward Deployed Engineer | New York or San Francisco (Onsite)
New York, NY · San Francisco, CANew York, NY +1On-site
$136,000–$216,000
Pay not posted
Pay not posted
$165,830–$243,142
Pay not posted
$167,000–$209,000
Cybersecurity AI Forward Deployed Engineer - FDE - Manager
Austin, TX · Milwaukee, WI · +39 moreAustin, TX +40
$80,400–$316,300
$180,000–$480,000
Pay not posted
$167,000–$209,000
$100,000–$130,000
$150,000–$200,000
Showing 15 of 753 matching postings. Open the full search and adjust filters →
- You already have the delivery experience FDE teams need, so the work is making it easy to evaluate.
- "Implemented a data platform" hides the answer — name whether you configured a product, wrote production code, or ran a migration.
- The exception you handled instead of forcing a customer onto the standard path is the strongest thing you can show.
- Read an AI requirement at the level of the work, because integrating a model and maintaining an AI platform are different jobs.
- Say what you have not shipped and ask whether onboarding covers it, rather than turning a prototype into production AI experience.
The experience to bring forward
Choose examples that carry both a technical boundary and a user boundary:
- a pipeline, integration or software workflow that reached regular use
- a user request you turned into a technical plan and a delivery sequence
- APIs, permissions, data-quality checks, testing, monitoring or incident resolution you owned
- a migration where you handled an exception instead of forcing the customer onto a standard path
- enablement or documentation that helped the customer operate the delivered system
Name the systems and the decision you made. State whether the work was a prototype, a proof of concept, a production deployment or ongoing operations.
A Veeam forward deployed engineer posting shows the range: customer deployments across cloud, hybrid and on-premises environments, integrations, data pipelines, automations, agent-based workflows, and security and governance requirements turned into technical plans.
Handling AI requirements
| What the posting asks for | What to prepare |
|---|---|
| Integrate a model into a production workflow | The data path, access controls, failure handling, and how the output is reviewed |
| Evaluate output against a benchmark | An evaluation set, the failure analysis, and what you changed as a result |
| Maintain an AI platform | Observability, cost and latency limits, rollback, and incident work |
| Build a new application | End-to-end design, from the user's task through monitoring |
If you have not shipped an AI system, describe the adjacent evidence plainly: data contracts, evaluation design, observability, access controls, rollback plans and production incident work. Then name the missing piece and ask whether the team supports it during onboarding.
How to write the transition story
Use one project to connect four points: the user's need, the systems you changed, the deployment or handoff, and the responsibility that remained. Also say what you did when the standard implementation failed. A concise account of the constraint, the options and the trade-off tells the team more than a list of products.
Five questions for the team
- Is the role mainly integrations, application development, configuration or model evaluation?
- Does the engineer own production incidents after the customer goes live?
- Which cloud, data and deployment environments are common in the customer base?
- How much of the role is writing code against configuring a platform or running enablement?
- What AI experience is required at hiring, and which gaps can onboarding support?
Frequently asked questions
What do FDE and deployment jobs asking for implementation and data engineering experience pay?
577 of 753 postings state a pay range. The median is $190,000, and half of them sit between $160,000 and $216,000, from 238 companies.
Which companies are hiring for FDE and deployment jobs asking for implementation and data engineering experience?
These 753 postings come from 341 companies. The employers with the most postings are Databricks (69), Deloitte US (61), Amazon (incl AWS) (31), Accenture (17) and Booz Allen (17).
Are FDE and deployment jobs asking for implementation and data engineering experience remote?
135 postings allow remote work from the US. Another 191 are hybrid and 126 are on-site. The remaining 301 say nothing about arrangement. Travel is mentioned in 379 of the 753 postings.
Counted over the 753 postings in this search. Postings read on October 24, 2026. These are the postings Nextmove tracks today, not a market survey.
Employer postings · Counted over the postings that state what experience they want. A posting that states none, or that asks for experience outside the five we list, is in none of them. · How we read postings