Join the world's leading real estate technology firms and take your career to new heights

Location: Argentina (Remote)

Compensation: Up to $2,000 USD/month

Language: Fluent English (required)

We are hiring a Senior AI Engineer with strong software engineering fundamentals and hands-on experience building production-grade AI systems.

This is a systems-level role. We are looking for someone who understands backend architecture, performance optimization, distributed systems, and clean engineering practices — and can apply those principles to LLM-powered and small language model (SLM) applications.

• Architect and implement scalable RAG systems (chunking strategies, embedding pipelines, retrieval tuning)
• Design service layers around LLM and SLM integrations
• Build and maintain MCP-compliant tool integrations
• Develop AI agents capable of multi-step reasoning and tool orchestration
• Implement and optimize small language model deployments (local inference, quantization, fine-tuning)
• Improve latency, cost efficiency, and reliability across AI systems
• Implement logging, evaluation, and guardrail frameworks for AI outputs
• Contribute to infrastructure decisions (cloud vs. local inference tradeoffs)

• 5+ years of professional software engineering experience
• Strong backend development experience (Python preferred)
• Solid understanding of:
• Distributed systems fundamentals
• API design and integration
• Data modeling
• Performance optimization
• Secure system design
• Hands-on experience with:
• RAG architectures
• Vector databases
• LLM APIs (OpenAI, Anthropic, Azure OpenAI, etc.)
• Small language models (e.g., Llama variants, Mistral, Gemma, etc.)
• Model quantization or local inference setups
• Experience building or integrating AI agents
• Fluent English (must be comfortable in technical discussions)

• Experience with model fine-tuning (LoRA, PEFT, etc.)
• Experience running models on local hardware (GPU nodes, on-prem inference, etc.)
• Familiarity with prompt injection mitigation and AI security
• Experience designing evaluation harnesses for LLM/SLM outputs

• Engineering maturity and architectural thinking
• Comfort balancing cost vs. performance trade-offs
• Ability to move from prototype to hardened production system
• Startup execution mindset