Hire AI Engineers Who Actually Ship
Forward deployed engineers, GTM engineers, LLM and agent builders, and full AI native teams. Vetted on real production work, and on your team in about [X] weeks.
The Problem We Solve
Getting an AI demo working is easy. Getting it into production, connected to your data, trusted by your teams and still working three months later is where most projects stall.
That gap is usually a people problem. You need engineers who have done it before, who know how to handle messy data, build evals, control costs and tell you when AI isn't the right answer.
That's who we place.Roles We Place
From a single forward deployed engineer to a full AI native team.
Forward Deployed Engineers
Engineers who sit with your business teams or your customers, understand the real workflow and turn it into a working AI system. Part engineer, part consultant.
GTM Engineers
Engineers who build your revenue engine. Automated prospecting, data enrichment, CRM workflows and AI agents that support sales and marketing at scale.
AI & LLM Engineers
RAG systems, fine tuning, prompt engineering and structured outputs on Claude, GPT, Gemini and open source models.
AI Agent Engineers
Multi step agents that use your tools, take real actions and have proper guardrails and human review built in.
Machine Learning Engineers
Forecasting, scoring, recommendation and classification models, trained and deployed at production scale.
MLOps & AI Platform Engineers
Evals, monitoring, cost tracking and deployment pipelines so your AI keeps working as usage grows.
Data Engineers
The pipelines and data foundations every AI project depends on.
AI Native Full Stack Engineers
Product engineers who build with AI tools every day and ship features faster because of it.
AI Solution Architects
Senior people who design the system, pick the right stack and keep the build on track.
Role Spotlight
The two roles teams ask us about most.
Forward Deployed Engineers
Most AI projects fail between the business and the build. A forward deployed engineer closes that gap. They join your team or go directly to your customers, map how the work actually gets done, and build AI solutions that fit into it.
Hire an FDE when you need to:
- Roll out AI across operations, finance, HR or support teams
- Deploy your AI product inside enterprise customer environments
- Turn a proof of concept into something people actually use daily
- Have one person own the problem from discovery to production
GTM Engineers
GTM engineers sit between sales, marketing and engineering. They build the systems that find the right accounts, enrich data, trigger outreach based on buying signals and keep your CRM clean, so your reps spend their time selling.
Hire a GTM engineer when you need to:
- Build signal based outbound and account prioritization
- Automate enrichment and lead routing in Salesforce or HubSpot
- Set up AI agents for research, personalization and follow ups
- Connect your GTM tools so data actually flows between them
Technology Stacks we cover
How You Can Engage
Add one engineer to your team, bring in a ready to go pod, or hire for the long term.
Staff Augmentation
Add one or more AI engineers to your existing team. They work in your tools, report to your leads.
AI Native Pods
A small, ready to go team (for example an FDE, AI engineer and data engineer) that takes on a specific outcome and delivers it.
Contract to Hire
Start on contract, then bring the engineer in house once you're confident.
Direct Hire
We find permanent AI talent for your team.
How We Vet
A strong resume doesn't mean someone has shipped AI to production. So every engineer goes through:
Technical Interview
With senior AI engineers, focused on production systems, not theory.
Practical Build Exercise
Based on a real world problem.
Shipped Work Review
Including what broke and how they fixed it.
Communication Check
Especially for forward deployed and client facing roles.
Only about [X]% of applicants make it through.
How It Works, from scoping call to start
Four steps between you and an engineer working with your team.
01. Scoping Call
Tell us the role, the outcome you need and your timeline.
02. Shortlist
You get [2 to 3] matched profiles within [X] hours.
03. Interview
You meet them directly and make the call.
04. Start
Your engineer is set up and working with your team within about [X] weeks.
Featured Engineers
Vetted, available and ready to interview.
Forward Deployed Engineer
8 years, 3 years in applied AI
Enterprise AI rollouts, RAG, workflow automation
Python, LangGraph, Azure OpenAI
US overlap
GTM Engineer
5 years
Signal based outbound, CRM automation, AI research agents
Clay, Salesforce, n8n, OpenAI
US overlap
Senior LLM Engineer
10 years, 4 years with LLMs
Agents, evals, cost optimization
Python, Claude, LangChain, AWS
EST
Onshore, Offshore or Both
Pair an onshore lead or forward deployed engineer who works closely with your stakeholders with offshore engineers who handle build and testing. You get faster delivery, work moving around the clock and a lower blended cost.