Tool design + integration
Typed tool schemas, retry / circuit-breaker logic, dead-letter queues, cost caps. Each tool is an integration; this is where most build time goes.
Hire AI Agent Engineers
Agent engineers — tools, orchestration, eval, safety.
AISD places agent engineers who specialize in production-grade multi-step AI systems. Tool design, orchestration patterns, eval-harness rigor, prompt-injection defense. Senior, pre-vetted, from $95/hour.
5–10 day staffing ·30+ production agents shipped · LangGraph · n8n · Pydantic AI
Specialties
Four agent-engineering specialties.
Orchestration patterns
Single-loop ReAct, plan-and-execute, multi-agent graphs (LangGraph). Picking the right pattern for the workload, not for novelty.
Eval + observability
Golden test sets, online metrics, distribution drift monitoring, weekly review rituals. Per-call observability on every model invocation.
Security + safety
Prompt-injection adversarial test suites, privilege separation, structured-output validation, human-in-the-loop on side-effecting actions.
Tooling our agent engineers default to
Mainstream stack. Pragmatic choices.
- LangGraph
- Pydantic AI
- Vercel AI SDK
- n8n
- OpenAI Assistants API
- Anthropic tools API
- LangSmith / Langfuse
- Modal / Inngest
We pick orchestration based on workload — n8n for ops-heavy automations, LangGraph for product-embedded agents, custom (TypeScript/Python with provider SDKs) for simple high-volume.
Frequently asked
Common questions.
How much does it cost to hire an AI developer?
Three pricing paths. AISD staff augmentation (senior, AI-native): $95–175/hour depending on seniority and engagement length. Marketplace contract (Toptal, Turing, Upwork): wide range — $40–200/hour with high variance in quality. Full-time hire (US): total comp typically $200k–$450k for a senior AI engineer. The hidden cost in hires is recruiting (3–6 months) and ramp (2–3 months). Staff augmentation pays off when you need impact in <90 days.
What's AISD's vetting process?
Every AISD engineer passes four gates. Technical screen — live problem-solving on AI engineering tasks (not generic LeetCode). System design — they design a production AI system end-to-end with one of our principals. Reference check — past clients confirm shipped production work. Paid trial sprint — a real, scoped piece of work with our team before the engineer faces a customer. Roughly 3% of applicants pass all four.
How is AISD different from a typical software development agency?
Three differences. First, every AISD engineer is senior — minimum 5 years building production software, with shipped AI features. Second, we publish hourly engagement bands and project ranges so you know roughly what an engagement costs before the first call. Third, we take fewer concurrent projects so a partner stays close to delivery.
How does pricing work — fixed-price, T&M, or retainer?
All three. Fixed-price for AI MVPs and agent builds where scope is well-defined after a discovery sprint. Time-and-materials for staff augmentation, billed monthly with a not-to-exceed ceiling. Retainer for ongoing optimization, eval-harness operations, and managed AI services — flat monthly fee for a defined scope of capacity.
How is success measured on an engagement?
Success metrics are defined in writing during scoping and reviewed monthly. Project engagements measure: feature shipped on date, eval-harness pass rate, target business metric (e.g. 'auto-resolve rate ≥35% on customer-support tickets'). Staff augmentation engagements measure: PR throughput, code-review acceptance, and customer-side satisfaction. We do not measure success in hours billed, lines of code, or generic velocity points.
How long does it take to build a production AI agent?
Working prototype: 2 weeks. Production-grade agent (with eval harness, guardrails, observability, and a runbook): 6–10 weeks. The prototype-to-production gap is where most projects fail — the prototype handles the happy path; production has to handle the long tail.
How long does it take to build an AI MVP?
Most AI MVPs at AISD ship a usable version in 4–8 weeks. Week 1 is a discovery sprint. Weeks 2–6 are the build, with weekly demos and a working version by week 4. Weeks 7–8 harden, document, and hand off.
How is AI consulting different from AI development?
Consulting produces decisions and plans; development produces working software. AISD does both, often in sequence: a consulting engagement scopes the architecture and roadmap, then a build engagement implements it. Consulting alone is right when you're early in the AI journey, evaluating vendors, or auditing existing work. Build alone is right when scope is already clear. Most AISD customers do a 2-week paid discovery sprint first — that's a consulting engagement that produces a fixed-price build proposal.