Production AI Engineer for Enterprise AI Workflows

Planet Paymet; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Planet is seeking an experienced engineer to lead the design, delivery, and maintenance of production AI workflows across HR, Finance, Operations and CRM. You will build agents, prompts, and retrieval pipelines, ensuring reliable, auditable decisions and continuous improvement through measurement and feedback.

You will own model behavior in production, defining success metrics and addressing edge cases, while collaborating with Data Engineering on infrastructure, CI/CD, and data governance.

Qualifications

• Strong software engineering background with production systems experience.
• Hands-on experience with AI/ML systems (LLMs, classifiers, decision models).
• Experience designing prompts, retrieval pipelines, or ML inference workflows.
• Comfortable with distributed systems and API integrations.
• Knowledge of model evaluation, monitoring, and feedback loops.

Responsibilities

• Design and build production-grade AI workflows that integrate internal systems (HR, Finance, Operations, CRM).
• Implement orchestration logic with triggers, retries, fallbacks, and human-in-the-loop patterns.
• Develop and maintain AI agents, prompts, retrieval pipelines, and decision logic.
• Own model behaviour in production: accuracy, failure modes, and edge cases.
• Iterate on model performance using evaluation frameworks and real-world data.
• Define and track success metrics such as accuracy, resolution rate, and time saved.
• Collaborate with Data Engineering on platforms, data pipelines, security and governance.

Skills

Python

Distributed systems

AI/ML systems

APIs

Prompt design

MLOps

Education

Bachelor's degree in Computer Science or related field

Tools

Temporal

Airflow

Step Functions

Job description

Planet is seeking an experienced engineer to lead the design, delivery, and maintenance of production AI workflows across HR, Finance, Operations and CRM. You will build agents, prompts, and retrieval pipelines, ensuring reliable, auditable decisions and continuous improvement through measurement and feedback.

You will own model behavior in production, defining success metrics and addressing edge cases, while collaborating with Data Engineering on infrastructure, CI/CD, and data governance.