Dedicated GenAI engineering talent
Hire generative AI developers and GenAI developers from Relevance Lab — for generative AI application development, RAG, agents, guardrails and evaluation, on a staff-augmentation basis or as a managed pod.
Quick answerGenerative AI developers from Relevance Lab build generative AI applications and copilots, retrieval-augmented generation pipelines, agent and tool-use workflows, guardrails and content filtering, evaluation harnesses, and integration with enterprise data — embedded in your team, model-agnostic across GPT, Claude, Gemini, Llama and Mistral.
What generative AI developers you hire build
GenAI applications & copilots
Purpose-built assistants and features for customer, employee and developer workflows.
RAG pipelines
Retrieval, grounding and citations over your documents and systems of record.
Agent & tool-use workflows
Multi-step tasks that call your systems, with approvals and tracing.
Guardrails & evaluation
Content filtering, hallucination and bias testing, and a versioned evaluation suite.
Staff augmentation or a managed pod
| Dimension | Staff augmentation | Managed pod |
|---|---|---|
| Direction | You direct named engineers | We run the team to an outcome |
| Composition | You choose the mix | Sized by us to the goal |
| Reporting | Into your leads | A pod lead reports to you |
| Switch later | Anytime | Anytime |
GenAI talent that ships responsibly
Responsible AI by default
Evaluation-first delivery, hallucination and bias testing, guardrails and HITL patterns.
Model-agnostic
The right model per use case, with a portable architecture.
Your process
Your repos, CI/CD, review and security from day one.
Platforms behind them
RLCatalyst and Spectra, plus a bench for spikes.
Vetted for depth
Real GenAI engineering, not adjacent skills.
You own the output
Code and configuration, in your environment.
- AWS
- DataStax
- Salesforce
- Snowflake
Prefer a fixed-scope build?
Generative AI Development Services deliver a defined outcome that we own from PoC to production.
How our GenAI teams work
Agentic AI vs Generative AI: key differences and enterprise use cases
Where generative AI ends and agentic AI begins — and which enterprise problems each is built for.
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Read MoreHire Generative AI Developers: frequently asked questions
Content last reviewed: September 2026
Scaling this across the enterprise?
Our Enterprise AI Services practice brings generative AI, agents and LLMs to production at scale — with the governance, platform and operating model to keep them reliable, compliant and cost-controlled.
Need generative AI engineers on your team?
Share the role, stack and timeline and we will send named candidate profiles within days.
Hire Generative AI Developers
Share the role, your stack and your timeline. We send named candidate profiles within days, and engineers typically start within 1–3 weeks — staff augmentation, team extension or a managed AI pod.