Hire Remote Forward Deployed Engineers For Teams Rolling Out AI Task Based, Hourly or Monthly
Fixed price per task, $70 an hour, or $10,000 a month
An engineer who joins your calls, repos and Slack, finds what is blocking the rollout, builds it into your systems and stays until your team uses it.
Discovery, deployment and adoption, owned by one remote engineer who works directly with your team.

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Forward Deployed Engineers From Empiric Infotech LLP
A forward deployed engineer (FDE) works with your team instead of behind a ticket queue. The engineer talks to the people doing the work, writes down the real problem, builds the fix into your systems and stays through adoption. Palantir made the role known, and AI companies now hire for it because a model is easy to demo and hard to deploy. Empiric Infotech LLP gives you that engineer remotely and ready for meetings outside regular development hours. Our engineers also write the tasks used to evaluate frontier AI models, so they know where models break before yours does.
What a forward deployed engineer delivers
Five things, from the first call to a rollout your team can run without help.
Discovery with the people doing the work
The engineer joins calls with operations, support, finance or whoever owns the process, watches how the work gets done, and writes up what to build first. You get a short written plan in the first week.
AI wired into the systems you already run
Your CRM, ERP, database, helpdesk and internal APIs, with scoped permissions, logs and an audit trail. The work lands in your repo and your cloud, on the model that fits: Claude, GPT, Gemini or open source.
Tests written before anything goes live
A test set built from your real cases, run again on every prompt or model change, so a quiet drop in quality shows up before a customer sees it. Our engineers use the same skill when they evaluate frontier models for AI programmes.
A rollout people actually use
Human approval where a mistake costs money, training for the team, a usage view for you, and a weekly review of where the system falls short. Adoption is part of the job.
A handover your team can own
Documented code, a runbook and a walkthrough with whoever takes over. Or the same engineer stays on for the next task.
How an FDE engagement starts
A call, a written task list, then work inside your team, usually within 48 hours of sign-off.
A 30-minute call
You describe the rollout, the systems involved and what is stuck. There is no charge for the call.
A task list with fixed prices
We break the work into tasks and give you a fixed price for each one. If the work is still taking shape, you can go hourly or monthly instead.
Access and a first working session
NDA and IP assignment come first. Then repo, cloud and Slack access, and a first working session with your team.
A weekly review
A written update and a live review each week: what shipped, what changed and what comes next. Meetings can run outside regular development hours when your team needs it.
Three ways to pay for a forward deployed engineer
Most FDE work is task based, with a fixed price for each task. You can also pay by the hour or take the engineer full time for a month.
Task based
- A fixed price for each task, agreed before it begins
- Good for a defined job: connect a system, ship an agent, run a rollout
- Meetings outside regular development hours are included
- A weekly review with the engineer
Hourly plan
- Billed by the hour, with time tracked and a weekly report
- Good for discovery, audits and short bursts
- Meetings outside regular development hours are included
- Stop any time
Monthly plan
- A forward deployed engineer full time, 160 to 172 hours a month
- Best when several tasks run one after another
- Your repo, your cloud, your model keys
- 7-day risk-free trial, monthly billing, seven days' notice to stop
The first 90 days with a forward deployed engineer
A typical path on a monthly engagement. Task work follows the same order at a smaller scale.
- Week 1
Discovery and a written plan
Access to your systems, calls with the people who do the work, and a plan that names the first task, the data it needs and how you will know it worked.
- Month 1
The first task live with real users
One workflow running in production for a small group, with tests in place, human approval on risky steps and a dashboard showing how it is used.
- Month 2
More systems and harder cases
The edge cases month one surfaced, the next integration, and a wider group of users. Training happens alongside the build.
- Month 3 and on
Your team runs it
A reliability and cost pass, a model swap if a newer one wins on your tests, documentation, and a decision on the next task or a handover.
A remote FDE compared with the other ways to get this done
| Empiric Infotech remote FDE | Your own FDE hire | AI consulting firm | A vendor's own FDE team | |
|---|---|---|---|---|
| Who does the work | An engineer who joins your team's calls and ships the code | An employee you recruit and manage | Consultants first, often a separate build team later | Engineers focused on their employer's product |
| How you pay | Task based, hourly or monthly | Salary plus employer costs; US job posts show a median of $195,000 a year | A project fee, usually after a paid assessment | Usually part of a larger contract |
| Time to start | Usually within 48 hours of sign-off | Months of recruiting in a tight market | Weeks of scoping | Depends on your contract |
| Choice of tools | Whichever model and tools fit your case | Your call | Often tied to partner vendors | Their own product first |
| After go-live | The same engineer tunes and extends it, or hands over | Stays while you keep the hire | A new statement of work | Support under your contract |
| What you own | All code, prompts and tests, in your repo | All of it | Per contract | Your configuration; the vendor owns the product |
The $195,000 figure is the median from 924 job posts (Recruiting from Scratch, June 2026), before employer costs. Other cells describe typical arrangements, and individual firms vary.
Working hours and meetings with your FDE
Our team works 09:30 AM - 07:30 PM IST and a project manager is on call 07:30 AM - 11:00 PM IST, Monday to Friday. Here is exactly when that lands for clients in the US, Europe and Australia, your region first.
US Eastern (New York, Boston, Atlanta) - full team online 11:00 PM - 9:00 AM (next day), project manager 9:00 PM - 12:30 PM (next day).
US Pacific (Los Angeles, San Francisco, Seattle) - full team online 8:00 PM - 6:00 AM (next day), project manager 6:00 PM - 9:30 AM (next day).
UK & Ireland (London, Dublin) - full team online 4:00 AM - 2:00 PM, project manager 2:00 AM - 5:30 PM.
Central Europe (Berlin, Paris, Amsterdam, Madrid) - full team online 5:00 AM - 3:00 PM, project manager 3:00 AM - 6:30 PM.
Australia East (Sydney, Melbourne, Brisbane) - full team online 3:00 PM - 1:00 AM (next day), project manager 1:00 PM - 4:30 AM (next day).
Want it to the half-hour in your own time? Slide through your day and book a slot below.
Why teams use Empiric Infotech for forward deployed work
A model demo takes an afternoon. Getting it to work with your records, your permissions and your people takes someone who will sit in the calls and read the messy data. That is the job.
Our engineers have shipped web, mobile and AI products since 2020: 375+ projects for 200+ clients in 25+ countries. They already work directly with clients, remotely, and join meetings outside regular development hours.
They also write tasks and scoring rubrics used to evaluate frontier AI models, where a professional completes the work and the model is tested against it. So they see first hand where models fail on real work. In your rollout, that shows up as tests written early and human checks placed where they matter.
AI products our engineers have shipped
Superintelligence: a conversational AI assistant
A conversational AI assistant with subscriptions, saved question history and an incognito mode, on OpenAI, Next.js, Node.js, Strapi, Firebase and Flutter.
Read case studyEndoDNA: an AI assistant over sensitive data
A HIPAA-compliant platform where clinicians ask an AI assistant about labs, DNA and patient history in plain language, with permissions for five user roles.
Read case studyTherapyCue: AI help during and after therapy sessions
Live transcription that fails over between providers, AI suggestions while the session runs and SOAP notes drafted when it ends, with audit tracking.
Read case studyOur Hiring and Engagement Model
Dedicated Resources
Hourly Basis
Hire a Forward Deployed Engineer As per Your Need
As a leading web and mobile app development company in the USA, Empiric Infotech LLP simplified the process of hiring web and mobile app developers. You can hire software engineers in 3 simple steps: Request, Interview, and Hire.
STEP 01
Request
Share your requirements
STEP 02
Interview
Take developer’s interview
STEP 03
Hire
Start risk-free work
What technical buyers say about Empiric Infotech
Frequently Asked Questions (FAQs)
An engineer who works directly with a customer's team to make software work in their real environment. An FDE finds out what is needed, builds it into the customer's systems and stays through adoption. The role combines full-stack engineering, integration work and client communication.
An FDE owns the outcome. A dedicated developer builds what your team has specified. An FDE also works out what to build, talks to the people affected, runs the rollout and measures whether it worked.
Three ways to pay: task based, hourly or monthly. The rates are in the pricing section on this page. For task based work, you get a fixed price before it starts.
You get a fixed price for each task before work starts. You approve it, the engineer does the work, and you can stop between tasks.
They work remotely, inside your Slack, repos and video calls. That covers the same daily contact with your team, and it means you can start in days.
Yes. Every engineer works directly with clients and can join meetings outside regular development hours, so your stakeholders can talk to the person building the system.
Usually within 48 hours of sign-off. A call, a written task list, NDA and IP assignment, then access to your systems and a first working session.
Whichever win on your tests at a cost that works: Claude, GPT, Gemini or open source models, with LangGraph, MCP or a plain function-calling loop. Most of the work is ordinary engineering around the model, in Python, Node.js and React.
You do, fully. An NDA and IP assignment are signed before work starts. Code, prompts and tests live in your repo, and model usage runs on your own accounts.
On our careers page at empiricinfotech.com/career. This page is for companies hiring an engineer.
GET A QUOTE NOW
Tell us what you want to deploy and what is in the way, and we will come back with a task list and a fixed price for each task.
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