Ortem Technologies

    Hire AI Developers

    Hire AI Developers Who Have Shipped

    Production LLM Engineers — Placed in 5–10 Days

    Hiring AI developers means finding engineers who have taken LLM features to production — RAG pipelines, agents, fine-tuning, evaluation — not tutorial graduates. We place pre-vetted AI engineers on your team in days, US-managed end to end.

    Book a Free Consultation See Our AI Agent Work
    Clients Worldwide
    300+
    Projects Delivered
    1,000+
    Rated on Clutch & GoodFirms
    5/5
    Years Experience
    13+

    The AI talent market has a signal problem: every resume now says "LLM experience," and most of it means API tutorials, not production systems. The engineers worth hiring are the ones who can talk concretely about retrieval evaluation, hallucination containment, token cost budgets, and what broke at scale — because they've been on call for it. That's what our vetting selects for. Every AI engineer we place has passed a live build session (a working RAG or agent feature, built in front of us) and can point to LLM features running in production.

    Hire an engineer, or hand us the build?

    If you have an engineering team and a roadmap, hire AI developers into it — they'll transfer capability to your team as they build. If you have an AI feature or product in mind but no team to absorb it, our AI agent development and LLM integration practices deliver it as a scoped project instead — and our own portfolio of 12 in-house AI agents shows the pattern quality you can expect. Between the two sits the dedicated AI pod: a self-managed team for a long-running AI roadmap.

    See our KnowledgeCore case study for the kind of production RAG engineering our placed AI developers are vetted against — 12,000+ ingested documents, role-based access, 1.4s p95 latency.

    Skills we place

    AI Engineering Roles We Fill

    From LLM application work to custom model engineering.

    • LLM application engineers (OpenAI, Anthropic, Gemini APIs)
    • RAG pipeline engineers (embeddings, retrieval, evaluation)
    • AI agent developers (tool use, orchestration, multi-agent)
    • Fine-tuning & prompt engineering with eval harnesses
    • MLOps engineers (serving, monitoring, cost control)
    • Computer vision engineers (PyTorch, YOLO, OCR)
    • Data engineers for AI (pipelines, vector databases)
    • AI product engineers (full-stack + LLM integration)

    Why Ortem

    Why Teams Hire AI Developers Through Us

    Production LLM Experience

    Engineers who have shipped RAG, agents, and LLM features to real users — with the evaluation and cost scars to prove it.

    Vetted on Real Builds

    Live coding on an actual RAG/agent task, not algorithm trivia. Communication evaluated as rigorously as code.

    Placed in 5–10 Days

    Skip the 4-month AI talent hunt. Pre-vetted candidates on your calendar within two weeks for most roles.

    US-Managed, IP-Safe

    US-enforceable contracts, NDAs, full IP assignment, and an account manager who checks in weekly.

    Current-Generation Stack

    GPT-5, Claude Opus 4.8/Sonnet 5, Llama 4, Gemini 3 — plus the orchestration and vector tooling around them.

    Which model fits

    Three Ways to Add AI Capability

    FactorHire AI DevelopersAI Project DeliveryAI Dedicated Pod
    What you get1+ AI engineers join your teamScoped AI build, fixed outcomeSelf-managed AI team on retainer
    Who owns deliveryYou — your process, your leadOrtem — owns the outcomeThe pod — owns sprints and backlog
    Time to start5–10 business daysAfter a scoping call7–14 business days
    Best forAdding AI skills to an existing teamA defined AI feature or productA long-running AI roadmap

    How it works

    From Role Brief to First Commit

    1. 01

      Define the Role (Day 0)

      A 30-minute call on what you're building, your stack, and what "senior" means for this seat. We draft the brief.

    2. 02

      Meet Candidates (Days 5–10)

      2–3 pre-vetted profiles with assessment results and links to production AI work they can speak to.

    3. 03

      Interview & Select

      You run your own technical interview — we facilitate scheduling. Your call, always.

    4. 04

      Onboard & Deliver

      Start within days of acceptance. Weekly account-manager check-ins keep integration and performance on track.

    FAQ

    Frequently Asked Questions

    Through Ortem, senior AI engineers run $45–$85/hour depending on specialisation — LLM application engineers at the lower end, ML engineers with fine-tuning and evaluation experience at the upper end. That compares with $150–$250/hour for equivalent US contract talent, and $200k+ salaries plus months of recruiting for in-house hires.

    Production LLM application work: RAG pipeline design (chunking, embeddings, retrieval evaluation), AI agent development with tool use and orchestration, fine-tuning and prompt engineering with evaluation harnesses, and MLOps (model serving, monitoring, cost control). Stacks include OpenAI and Anthropic APIs, LangChain/LlamaIndex, vector databases (pgvector, Pinecone, Weaviate), and PyTorch for custom model work.

    Three stages: a technical assessment covering LLM fundamentals and system design, a live coding session building a working RAG or agent feature (not whiteboard trivia), and a communication evaluation. We look specifically for engineers who have shipped LLM features to production users — handling hallucination, latency, cost, and evaluation — not just completed tutorials.

    For LLM application engineers (RAG, agents, API integration), we present pre-vetted candidates within 5–10 business days. Deeper ML specialisations — custom fine-tuning, computer vision, on-prem model deployment — typically take 10–15 days. You run the final interview and make the call.

    Related Services

    AI Agent DevelopmentLLM IntegrationStaff AugmentationDedicated Team

    Further Reading

    Hire AI Developers GuideAI Agents PortfolioLLM Integration CostCase Studies

    Need AI Engineering on Your Team?

    Tell us the role. Pre-vetted AI engineers with production LLM experience, on your calendar within two weeks.

    Book a Free Consultation

    Also see: AI Agent Development · LLM Integration · AI Portfolio