Forward deployed engineers — Netguru

Forward deployed software engineers for hire

Embed a vetted AI engineer directly inside your team. Outcome-accountable from day one — no hand-holding, no ramp-up lag.

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Proven at scale — across industries

Unlike other agencies, Netguru provides the full spectrum of talent you need to achieve stable, long-term success.

400+

Engineers and specialists available for embedding

4.9/5

Average client rating on Clutch

83%

Reduction in claims processing time — ARC Europe

20×

Faster R&D cycle delivered for Merck KGaA

Trusted by global brands

Whether you want to consult an idea, add missing capabilities, quickly expand your team, or hand over a project – we’ve got you covered.

What is a forward deployed engineer?

A forward deployed engineer (FDE) works embedded inside your organisation rather than from a vendor's office. They own implementation end-to-end: understanding your data, your workflows, and your team’s constraints — then building and shipping AI that actually fits.

The embedded engineer model is now being scaled by OpenAI, Anthropic, and Salesforce to drive enterprise AI adoption. When Netguru provides an FDE, you get that same embedded accountability — without the in-house hiring cost, equity dilution, or 6-month recruitment timeline.

What your forward deployed engineer delivers

Every Netguru FDE owns a problem end-to-end — from architecture to production. Vetted across the full AI stack.

LLM & GenAI engineering

Prompt engineering, RAG pipelines, fine-tuning, and production LLM deployment — shipped into your stack, not handed back as a spec.

ML model development

Custom model training, evaluation frameworks, and continuous improvement loops tied to your business KPIs — not academic benchmarks.

MLOps & AI infrastructure

CI/CD for models, drift detection, and scalable inference pipelines — so your AI keeps working in production, not just in the demo.

AI architecture & system design

Technology selection, integration planning, and end-to-end system design that fits your existing data and team constraints.

Data science & analytics

Feature engineering, experimentation design, and business-ready insights extracted from your data — not generic industry benchmarks.

AI product management

Roadmap definition, stakeholder alignment, and translating business problems into shippable AI specs that engineers can act on.

ARC Europe cut claims processing time by 83% with an embedded Netguru engineer

AI automation · Insurance.

Technologies: Python, LLM-based AI agent, HubSpot CRM integration.

Client expectations: Transform a 30-minute manual claims process into something that could scale — without a long procurement cycle or a standing internal AI team.

Result of the partnership: Netguru embedded an AI engineer directly inside ARC Europe's operations team — analysing workflows, building an AI agent, and shipping it into production. Claims processing time dropped from 30 minutes to 5 minutes. 83% reduction in processing time.

ARC Europe — AI claims processing case study

20× faster R&D cycle — Merck KGaA

Merck KGaA needed to cut chemical compound identification time from a 6-month manual research cycle to something that could run at AI speed. A Netguru AI engineer embedded inside their R&D team — mapped the data constraints, built a custom LLM-based assistant on their secure AWS infrastructure, and delivered a production PoC in 5 weeks. Chemical identification time: 6 months → 6 hours.

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Merck AI R&D orange square preview 2

If I had to choose two words to summarize our collaboration with Netguru it would be speed and efficacy.

Mark Greiner

Digital Innovation Manager at Merck KGaA Darmstadt

Get matched with a forward deployed engineer in days — not months

Tell us your stack, your use case, and your timeline. We'll shortlist engineers with the exact domain experience you need — no padded proposals, no 6-month search. Most engagements start within 2–4 weeks.

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What engineering leaders say

In our clients' words

It doesn't feel like an external team, it feels like we're just working together.

Dally Singh

Chief Product Officer, Total Processing

I'm especially happy that both teams collaborate so smoothly that it feels like a single team.

Kasparas Kralikas

Engineering Manager, Vinted Go

The Netguru team has gone above and beyond any expectations of what a strong and reliable partner can be.

Hima Mandali

CTO, Solaris SE

Frequently asked questions

Everything you need to know before embedding a forward deployed engineer in your team.

What exactly is a forward deployed engineer?

A forward deployed engineer is a software or AI engineer who works embedded inside a client's organisation rather than building from the outside. They own the full implementation cycle — from scoping and architecture to deployment and iteration — and are directly accountable for outcomes, not just deliverables.

How is this different from AI staff augmentation?

AI staff augmentation typically adds multiple specialists to your team across different roles (ML engineers, data scientists, MLOps). A forward deployed engineer is a single senior operator with broad ownership — closer to having a founding engineer embedded in your team than a contractor filling a gap. They own the problem, not just the task.

How quickly can an FDE start?

For most engagements, we can match and onboard a forward deployed engineer within 2–4 weeks. We shortlist candidates against your tech stack, domain, and timeline requirements before any introductions — so time spent in the process is minimal.

Does the FDE come with a tech lead or support team?

Yes. Every Netguru FDE is backed by our internal engineering community — architecture review, code standards, and escalation paths are built in. For larger engagements, we can also pair the FDE with supporting specialists (data engineers, MLOps, QA) as the scope evolves.

What engagement models do you offer?

We offer full-time embedding (standard), part-time advisory (2–3 days per week), and project-based engagements with a defined scope and timeline. We'll recommend the right model after an initial scoping call — most clients start full-time and adjust as the AI product matures.

How much does a forward deployed engineer cost?

Netguru FDE engagements are structured on a Time and Materials basis — you pay for actual engineering hours rather than a fixed project estimate. Most full-time FDE engagements start at a monthly retainer; part-time advisory and project-based scopes are also available. We'll share transparent rate information on an initial scoping call once we understand your stack and timeline.