AI Engineer

About the Role

Monaco is building an AI-native revenue platform that replaces the fragmented GTM stack (CRM, sequencing, call recording, enrichment, pipeline management) with one unified system. We’re consolidating 6–10 disconnected tools into a single, purpose-built platform and redefining what’s possible when all the data lives under one roof in the age of AI - this is a category-defining shift, not an incremental improvement.

We launched publicly in Feb 2026 and are 50 people and growing. We have strong early product-market fit, creating millions in ARR in only a few months post-launch.

We're looking for an AI Engineer to help turn modern foundation models into real, reliable product features. This role is about applied AI - prompts, orchestration, retrieval, and product integration - not training models from scratch. You'll work closely with product and design to build AI capabilities that users actually trust and use every day.

What you'll do:

• Build LLM-powered product features using prompt engineering, structured outputs, and tools.
• Build and iterate on RAG systems (chunking, embeddings, retrieval, prompt composition).
• Orchestrate multi-step AI workflows: agents, tools, memory, retries, fallbacks.
• Evaluate quality, latency, and cost - and continuously improve reliability.

What we're looking for:

• 3+ years building AI-driven or ML-adjacent product features.
• Strong hands-on experience with LLMs (OpenAI, Anthropic, or open-source).
• Solid Python skills and experience integrating AI into backend systems.
• Product-minded: you care about UX, speed, and real-world constraints.

Nice to have:

• Experience building agentic systems with tools and memory.
• Familiar with vector databases and embedding models.
• Some exposure to fine-tuning or adapters.

Location:

San Francisco. We're an in-person team - 5 days in the office. At this stage, proximity genuinely accelerates product quality and team cohesion.