Senior AI engineers who work inside your team
AI FDE as a Service (Forward Deployed Engineer as a Service) means we place a senior AI engineer, or a full pod, directly inside your team. They join your Slack, your standups, your roadmap, and ship production AI features every two weeks. Monthly retainer, not a 12-month contract.
Stop losing another quarter waiting for the perfect AI hire. Get a senior engineer embedded in your team next week, productive from day three, shipping by day fourteen.
The problems this solves
The situations where clients usually bring us in.
Senior AI talent is almost impossible to hire
Average time-to-hire: 4-6 months. Competing offers from FAANG, burn rate climbing. Meanwhile, your competitors are shipping.
Consultants don't stay long enough to understand you
Traditional consultants deliver a slide deck, then leave. An FDE works inside your business, learns your data, and ships what helps.
Outsourcing AI rarely produces production code
Agencies deliver prototypes that fall apart in production. FDEs write the code your team will maintain, in your repo, to your standards.
Leadership keeps saying 'try AI', but nothing ships
Your team is already stretched. They don't have bandwidth to learn LLMs, evals, vector DBs, and agent frameworks while also keeping the business running.
What's delivered at the end
Every engagement ends with these in your hands.
A named senior engineer (or pod) embedded in your team
Not a pool of anonymous offshore devs. A specific, senior person you meet and approve, who learns your business and stays with you.
Shipping velocity from week one
FDEs bring a toolkit of proven patterns (RAG stacks, agent frameworks, eval harnesses, deployment templates), so they skip 4 weeks of setup.
Code that lives in your repo
Every line is in your GitHub, on your standards, reviewed by your team. Nothing hidden in a black box.
Month-to-month flexibility
Scale the pod up for a big launch, down after. Pause during a quiet quarter, with no penalty or long contract.
From first call to live in production
Match & approve
We propose a specific engineer based on your stack and domain. You interview them like you would any hire, and approve before they start.
Embed & onboard
Week one: they join your Slack, standups, and tools. Access to code, data, roadmap. We handle NDA and IP assignment.
Ship in 2-week sprints
Clear sprint goals, weekly demos, production deploys. You review output exactly like any team member.
Scale or graduate
Add more FDEs, replace with a dedicated internal hire we help recruit, or stay on retainer as long as it's useful. You decide.
- Day 1Sprint goals agreed
- Week 1Weekly demo
- Week 2Weekly demo
- Day 14Shipped to production
- Production code
- Tests & CI
- Docs & runbooks
- You own all of it.
Under the hood
For the CTO, tech lead, or engineering manager evaluating us: here's how we build.
AI stack breadth
LLMs (OpenAI, Anthropic, Gemini, open-source via litellm), RAG (Pinecone, Weaviate, pgvector, Qdrant), agents (LangGraph, CrewAI, Pydantic AI, custom), eval (LangSmith, DeepEval, Ragas).
Full-stack engineering
Python, TypeScript, Next.js, FastAPI, Go when needed. Postgres, Redis, Kafka, Snowflake. Terraform for infra. Everything we write is meant to run in production.
MCP & tool integration
Building MCP servers to expose your internal tools to agents safely. Structured tool-use, authorization, audit logs.
Self-hosted & on-prem
For data-sensitive clients: vLLM, llama.cpp, local Qwen/Llama deployments, self-hosted vector DBs. Your data never leaves your infrastructure.
Evals, observability, CI
Every feature ships with an eval suite, tracing, cost/latency dashboards, and CI checks that catch regressions before deploy.
Security & compliance posture
Zero-retention API providers by default, PII masking, PDPA and GDPR-aware data handling, and SOC 2-style control patterns. We work inside your compliance boundary.
You'll walk away with
- Named senior AI engineer(s) embedded in your team
- Shipped, production-quality features every sprint
- All code in your repository with full IP assignment
- Sprint demos, weekly written updates, monthly executive reviews
- Runbooks, documentation, and handover to your team on exit
- Access to the wider RNA engineering team for peer review on hard problems
This is a fit if…
- Product or engineering leaders who need AI shipped this quarter, not next year
- SaaS companies adding AI features to existing products
- Enterprises piloting AI internally (search, summarization, analysis, automation)
- Funded startups that need a senior AI hire but can't wait months to find one
- Teams that tried hiring an AI engineer and couldn't find one that fit
AI FDE as a Service is priced as a monthly retainer per engineer (or pod), typically 50-70% of the total cost of a comparable full-time hire, with no recruiting fees, no equity dilution, and the option to transition to a permanent hire if you want. Book a consult for a concrete number.
Questions we hear most often
What does 'AI FDE' mean?
FDE = Forward Deployed Engineer. The term was popularized by Palantir: an engineer who doesn't sit in a central R&D lab, but works forward-deployed inside the customer's environment. An AI FDE brings that same hands-on, embedded model to AI engineering, inside your Slack, your codebase, your business.
How is this different from a normal consultant or agency?
A consultant usually hands over a report, and an agency usually builds a prototype and moves on. An FDE works inside your team and ships production features that you own the code for. We judge our work by what gets merged into your main branch.
Who does the work?
Named senior engineers with at least 5 years of production experience, most with a decade or more. You meet them before you sign. We do not subcontract out or swap people mid-engagement without your approval.
What time zones do you work?
Our engineers overlap at least 4 hours a day with your core working hours. Most clients are in Southeast Asia (SGT/WIB) or the US (ET/PT), and we staff accordingly.
What happens to the code if we stop the retainer?
You own it. All of it. Code is in your repo from day one, with an IP assignment clause in the contract. If you stop tomorrow, your team keeps shipping with what we built.
Can you help us eventually hire in-house?
Yes. Many clients use us as a bridge: the FDE ships AI while we help them interview, hire, and onboard a permanent senior engineer. We stay as long as we're useful, then hand over cleanly.
Do you sign NDAs, DPAs, MSAs?
Standard practice from day one. We also carry professional indemnity insurance and are happy to sign your standard supplier documents or our own templates, whichever is faster for your legal team.