Hire Dedicated LLM Engineers — India, US, UK & Australia
Hire pre-vetted LLM engineers who ship production RAG systems, agents, and fine-tuned models — not just prototypes. Golonex places dedicated India-based LLM engineers with US, UK, Australian, and Indian teams — working in your timezone, under NDA, onboarded within one week and with no lock-in.
What a LLM Engineer does
An LLM engineer builds applications on top of large language models — retrieval-augmented generation (RAG), agents, and fine-tuned models. Day to day they design chunking and embedding pipelines, wire vector databases, engineer and evaluate prompts, orchestrate tool-using agents, fine-tune or adapt models with LoRA, and put guardrails, evals, and cost/latency controls around it all for production.
Core expertise
What a Golonex LLM Engineer builds for you
How it works
Engagement models
Based in India, working in your timezone. Onsite options available across the US, UK, and India.
Category
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Data, AI & ML Engineers
The Golonex difference
Named, pre-vetted engineers
Every LLM Engineer is screened for technical depth, communication, and reliability before you meet them — a sub-30% pass rate at the technical stage.
Integrated within 1 week
From enquiry to working team member in 5 business days. We handle onboarding, NDA, and access logistics.
Your timezone
India-based talent working overlapping hours with US, UK, and Australian teams. Daily standups and real-time collaboration, agreed upfront.
NDA-protected, no lock-in
Full IP and confidentiality protection as standard. Month-to-month engagements — scale up or down as your project evolves.
Hiring a LLM Engineer — FAQs
How quickly can I hire an LLM engineer through Golonex? +
Typically within one week. We shortlist pre-vetted LLM engineers matched to your need — RAG, agents, or fine-tuning — you interview them, and the selected engineer is onboarded to your stack and tooling within 5 business days, working in your timezone.
Do you build with commercial APIs or open-source models? +
Both. Our LLM engineers work with OpenAI and Anthropic APIs as well as open-source models via Hugging Face and self-hosted inference, choosing based on your privacy, cost, and latency needs. Tell us your constraints and we match accordingly.
Who owns the models, prompts, and code you build? +
You do. All prompts, pipelines, fine-tuned weights, and application code produced in the engagement are your intellectual property, and everything is delivered under NDA. We retain no rights to your data or outputs.
How do you keep LLM outputs accurate and safe? +
Our engineers build evaluation harnesses, grounding via RAG, structured outputs, and guardrails for hallucination, PII, and prompt-injection risks. They measure quality against your test set so improvements are evidenced, not assumed.
How do you vet LLM engineers? +
Every candidate passes a technical assessment on real scenarios — RAG design, embedding and retrieval tuning, and agent orchestration — plus a communication and remote-working assessment and reference checks from at least two prior engagements before you meet them.
Ready to hire a LLM Engineer?
Tell us the role, stack, and timeline. We'll match you with a named, pre-vetted engineer — integrated within 1 week.