Applied AI Engineer

Responsibilities

• Design and implement agent improvements including prompting strategies, tool selection, action planning, and memory usage
• Build robust evaluation pipelines for offline evals, online metrics, and experimentation frameworks
• Productionize applied LLM techniques such as function-calling, self-reflection, RAG, and multi-agent handoffs
• Improve core backend systems including job orchestration, scalable memory, and data pipelines for Gmail, Slack, and Notion
• Partner with product and infra teams to define success metrics and ship iterations
• Write clean, well-tested code and document design decisions

Requirements

• 4+ years of backend engineering experience, preferably with Python
• Hands-on experience with LLMs, prompt engineering, function-calling, and retrieval
• Proven track record of building evaluation harnesses and driving improvements
• Solid understanding of distributed systems, concurrency, and reliability
• Experience with pragmatic experimentation and hypothesis-driven development
• Strong debugging and instrumentation skills

Preferred Qualifications

• Experience with agent frameworks and tool orchestration
• Production experience with RAG systems
• Proficiency with Redis, Postgres/Supabase, and task queues like Celery or SQS
• Experience with observability stacks like Datadog or OpenTelemetry

About the Company

Cofounder is building autonomous agents designed to run entire businesses.