AI Engineer- agentic startup- $300,000-$350,000 base + bonus!

Saragossa; Los Angeles (CA); On-site; USD 140,000 - 230,000; Full time

Job summary

Saragossa is seeking multiple AI Engineers to shape its decision intelligence platforms. You will lead the evolution of AI capabilities across RAG, LLMs, MCPs, and ontology and work with product teams to turn large, unstructured data into reliable insights.

You should have shipped AI-powered features in startup or SaaS environments, with a track record of delivering production-ready systems and reliable model behavior. If you’ve brought AI from theory to production, you’ll thrive here.

Qualifications

• Shipped AI-driven features in startup or SaaS environments.
• Reimagined systems using agentic patterns.
• Built decision-support tools delivering business value.

Responsibilities

• Lead evolution of decision intelligence systems across RAG, LLMs, MCPs, and ontology.
• Apply LLMs, vector retrieval, and AWS-native AI tools to transform unstructured data into actionable insights.
• Collaborate with product teams to map real customer use cases and drive AI initiatives.

Skills

AI engineering

LLMs

RAG

Vector retrieval

AWS

Production deployment

Data normalization

Decision intelligence

Tools

AWS

Vector databases

RAG tooling

Job description

Looking to take on a high-impact AI engineering role where your work shapes how thousands of firms make decisions every day?

If you're interested in building the next generation of AI-powered SaaS platform- transforming how firms automate workflows, normalize data, surface insights, and drive intelligent decision-then this could be a great next move for you.

They’re searching for multiple AI Engineers to lead the evolution of their decision intelligence systems across RAG, LLMs, MCPs, and ontology.

In this role, you’ll apply advanced LLMs, vector retrieval, and AWS-native AI tools to turn massive and unstructured datasets into reliable, repeatable, high-utility intelligence. You’ll work closely with product teams to understand real customer use cases, normalize and unify data from multiple sources, and design decision-support engines that can eliminate hallucinations, maintain cost efficiency, and power operational transformation.

They’re looking for someone who has shipped AI-driven features in startup or SaaS environments, reimagined existing systems using agentic patterns, and built decision-support tools that materially improved customer experience or operational efficiency. If you’ve taken AI from theory to production, navigated the challenges of reliability and model behavior, and built systems that deliver real business value, you’ll thrive here.

No up-to-date resume required.