About the Role

We are seeking a highly experienced Senior Private AI Platform Lead to design, build, and operate a secure enterprise AI platform powered by open-weight Large Language Models (LLMs) deployed entirely within company-controlled infrastructure.

This role is responsible for enabling enterprise AI capabilities without reliance on external SaaS AI providers, leading the deployment, optimization, governance, and operation of self-hosted LLMs, AI agents, and inference platforms in highly secure environments.

Key Responsibilities

- Design and lead the architecture of a private enterprise AI platform.
- Deploy, optimize, and operate open-weight LLMs in company-owned infrastructure.
- Build and support AI solutions using agents, RAG architectures, and tool-calling frameworks.
- Implement scalable inference and model-serving environments.
- Partner with Infrastructure, Security, and Enterprise Architecture teams.
- Manage AI workloads running on Kubernetes and GPU-based environments.
- Establish observability, monitoring, governance, and operational standards for AI systems.
- Drive AI Platform Engineering and MLOps best practices across the organization.

Required Qualifications (Must-Haves) Open-Weight LLM Experience

Hands-on experience working directly with open-source/open-weight models such as:

- Llama
- Qwen
- Mistral
- Mixtral
- DeepSeek
- Gemma

Candidates whose experience is limited to OpenAI, Claude,



Gemini, or similar APIs will not be considered. LLM Deployment & Inference Platforms

Demonstrated experience deploying and operating LLMs using technologies such as:

- vLLM
- SGLang
- llama.cpp
- Ollama (preferred)
- Quantization techniques
- Tensor Parallelism

Advanced Python Development Strong hands-on experience with:

- Python
- PyTorch
- Hugging Face Transformers
- PEFT
- Accelerate

Model Fine-Tuning Experience

Proven experience with

- LoRA
- QLoRA
- Adapter-based training
- Model evaluation and benchmarking
- Prompt optimization

AI Infrastructure & Platform Engineering Experience operating production environments with:

- Kubernetes
- Docker
- Linux
- NVIDIA GPU infrastructure
- Monitoring and observability platforms

AI Agents & RAG Architectures

Practical experience building

- Agentic systems
- Tool-calling frameworks
- Model Context Protocol (MCP)
- Retrieval-Augmented Generation (RAG) solutions
- Multi-agent workflows

Secure & Private AI Environments

Experience working within

- Self-hosted AI environments
- Private AI deployments
- Security-sensitive infrastructures
- Air-gapped or offline environments (strongly preferred)

We are seeking a hands-on technical leader who has built, deployed, and operated private AI platforms using open-source LLMs in enterprise environments.

📌 Senior Private AI Platform Lead (México)
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