Hire an AI agent engineer who ships agents into production.
An engineer who takes agent workflows past the pilot stage and into daily use.
Agent projects fail on the unglamorous parts: permissioning, evaluation, fallbacks, and integration into the systems where the work actually happens. Our agent engineers specialize in exactly that — the discipline that separates a shipped agent from a stalled pilot.
- Seniority
- 5+ years, 1+ years specifically on production agent systems
- Background
- Multi-step agent workflows, human-in-the-loop design, guardrails, and integration into CRM/ERP/ticketing systems
What they'll actually do.
Not a job description — the work this person owns from their first sprint, inside your codebase and your process.
Work this bench has shipped.
AI Support Agent for a DTC Ecommerce Brand
A production support agent handling order status, returns, and product questions across email and chat — integrated with Shopify and the brand's 3PL, with human escalation built in.
Cove — Home Security Platform Consolidation
Operator portal, headless CMS, and marketing platform for a US home-security device ecosystem — three disconnected systems consolidated into one operator experience.
Vaisela — AI Virtual Seller Assistant for Amazon
An AI-powered virtual assistant for Amazon sellers: a custom-trained LLaMA model analyzes Seller Central data and proactively recommends actions — privacy-by-design, piloted with 200 sellers, architected to scale to millions.
Tell us the role, the stack, and when you need them started.
Every figure has a name behind it.
No rounded-up vanity metrics — each number below is tied to a specific, named engagement this bench shipped.
From intro call to embedded.
Matched by the same engineers who ship our own agent rescues — they know exactly what separates a shipped agent from a stalled pilot.
Intro call
Confirm the role, stack, and team fit in one call.
Match
We propose 1–2 engineers from the bench who fit the work, not a generic pool.
Trial week
A real first week of work before any longer commitment.
Embed
Full participation in your standups, sprints, and tooling.
If the fit isn't right, we replace them inside two weeks — no argument, no fee for the swap. You'd rather we caught it early, and so would we.
The team runs like an extension of our engineering org — weekly delivery, transparent metrics, real ownership.
Asked on every first call.
Agent systems fail differently from ordinary backend systems — on permissioning, escalation design and guardrails rather than on code quality alone. An AI agent engineer owns that specific discipline: deciding what the agent may do unsupervised, where a human gate belongs, and how the workflow behaves when a step fails rather than when it succeeds.
Yes, and that is the default. A staff-augmentation AI agent engineer works inside your codebase, your process and your standups, not in a separate vendor environment.
An AI agent engineer typically starts within one to two weeks of the intro call. We match from an existing bench rather than opening a cold hiring pipeline, so the limiting factor is usually your onboarding and access paperwork rather than our recruiting.
Every AI agent engineer placement carries a two-week replacement guarantee, with no argument and no fee for the swap. We would rather replace someone in week two than have you carry a bad fit for a quarter.
No. An AI agent engineer is engaged day-rate or monthly, month-to-month after a four-week minimum. No tiers, no bundled products, no notice period designed to trap you.
You do, from the first commit. An AI agent engineer works in your repositories under your version control, and all work product assigns to you — agent and tool-definition code, guardrail and evaluation suites, and documentation. The IP assignment is signed before anyone is given repository access, not negotiated at handover.
One call. Then a name, not a pipeline.
- 30 minutes with a senior engineer, not a recruiter
- Free and no-obligation — bring the role and the stack
- You leave knowing who we'd match and how fast they can start
- We reply within one business day
Anthropic-certified engineering capacity for Claude-native products and agents.
Senior LLM application engineering, without the vendor lock-in.
Full-stack web and mobile engineering, AI-accelerated, senior-owned.
Fractional technical leadership for teams that need direction, not headcount.
Fractional AI leadership — roadmap, governance, and vendor decisions.
Retrieval pipeline engineering — the discipline behind every trustworthy RAG system.
Deployment, monitoring, and cost control for production AI systems.
Pipelines, warehousing, and AI-ready data infrastructure.
Systematic prompt and context design, tested against real outcomes.
Product management for AI features and roadmaps, grounded in what's actually feasible.
Let's put AI to work in your business.
A 30-minute call. You bring the workflow or the roadmap — we'll tell you what's feasible, what it costs, and what we'd build first.