Applied AI Engineer

About the Role

A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time.

As an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production.

This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real-world usage.

Focus:

• Build and ship AI features end-to-end (model to system to user experience)
• Design and iterate on prompts, tools, memory, and agent workflows
• Turn raw model outputs into structured, reliable, and predictable behaviors
• Debug issues across the full stack (model, orchestration, infra, UX)
• Optimize for latency, cost, and production reliability
• Develop lightweight evaluation frameworks to measure real-world performance
• Work closely with product and engineering to translate ambiguous problems into working systems

Tech Stack:

• Python
• PyTorch / JAX
• LLMs (OpenAI-style APIs, LLaMA, Qwen, etc.)
• Inference / serving (e.g. vLLM)
• Vector DB

Ideal Experience:

• Strong foundation in machine learning and modern neural network architectures
• Hands-on experience with training, fine-tuning, or deploying ML models
• Ability to write clean, production-quality code
• Comfort working across abstraction layers (model to infra to product)
• Strong problem-solving skills in ambiguous, fast-moving environments
• Bias toward shipping, iteration, and continuous improvement