Hire AI Engineers
Senior AI engineers shipping LLM agents, RAG pipelines, and production-grade AI features — not weekend GPT wrappers.
Senior AI engineers who've shipped LLM systems to production — with eval suites, observability, cost ceilings, and fallback logic. The difference between a great demo and a customer-trusted product is the boring infrastructure; that's where we live.
Built for teams that need senior engineering — fast.
- AI startups going from prototype to production
- SaaS adding AI features that need to actually work at scale
- Operators automating document workflows, support, or sales
- Teams whose 'just plug in OpenAI' broke under real users
Concrete deliverables. No bench-warming.
Production RAG pipelines
Hybrid retrieval, reranking, eval-driven chunking, freshness handling. Not the demo; the version that works for paying customers.
Production agents on LangGraph
State machines, retries, deterministic fallbacks, schema-validated tool calls, prompt-injection defences, cost ceilings.
Eval infrastructure first
Golden test sets, automated regression on every PR, production sampling, human-in-the-loop scoring. Deploys gated on eval health.
Multi-model strategy
OpenAI, Anthropic, open-weights via Bedrock / Together. Per-task routing, no provider lock-in, swap without rewrites.
Fine-tuning where it pays off
Honest assessment first. We fine-tune when you have repeatable structured tasks at scale — not when better prompting would do.
Cost + observability
LangSmith / Helicone tracing, per-session cost dashboards, hard ceilings, alerts. Burn rate becomes a metric, not a roulette.
Pick the shape that fits.
Project-based
Fixed scope build of an AI feature or product.
Staff augmentation
Senior AI engineer embedded in your team for 3+ months.
Retainer
Ongoing AI engineering — features, evals, model upgrades.
AI audit + roadmap
Audit of your current AI system: eval coverage, cost, observability, with prioritised remediation plan.
Tools our AI / LLM engineers reach for.
Common questions about hiring AI / LLM engineers.
Are these engineers really senior or junior fronts?+
Senior. Average 5+ years in ML/AI, 2+ years shipping LLM systems to production, with eval and observability discipline. We don't pad engagements with juniors.
Can you take over a flaky AI feature we already shipped?+
Yes — that's a big chunk of what we do. We audit eval coverage, cost, observability, prompt versioning, and fallback logic, then propose a remediation plan with concrete priorities.
Do you fine-tune models?+
Yes when it's the right call. We assess fine-tune vs RAG vs better prompting honestly. Most early projects don't need fine-tuning; the ones that do, we ship.
Will you keep our data out of model training?+
Yes. We use enterprise tiers (OpenAI, Anthropic) with contractual training opt-out, or self-host open-weights for the most sensitive workloads.
Ready to hire AI / LLM engineers?
Send us a brief, we send 1–2 candidate engineers to interview within 7 business days. No long sales cycles.