AI Engineer

Posted Yesterday
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4 Locations
In-Office
Mid level
Information Technology • Consulting
The Role
Design, build, and maintain production AI workflows (agents, prompts, retrieval pipelines) integrating HR/Finance/Operations/CRM. Own orchestration, monitoring, evaluation, and continuous improvement to ensure reliable, auditable decision quality and measurable business outcomes.
Summary Generated by Built In

About Us

Planet is a leading technology company transforming payments by putting customer experience first. We offer integrated solutions that include payment processing, VAT refunds, dynamic currency conversion, and management services for merchants in the Retail and Hospitality sectors worldwide.

In recent years, we have experienced significant growth, expanding our services and global presence.

With strong private equity investors, Advent International and Eurazeo, we have the financial capital and expertise to grow our capabilities and reach through acquisitions.

Our mission is to create a world of connected commerce where payments are simple, secure, and seamless, enabling our partners to deliver exceptional experiences to their customers.
 

Role Overview:

This role owns the design, delivery, and ongoing behaviour of production AI workflows that automate and augment work across Planet’s internal systems — HR, Finance, Operations, and CRM. You will be accountable not only for shipping the technology, but for the quality of the decisions it makes: building agents, prompts, and retrieval pipelines that business users can trust, and improving them over time through measurement and real-world feedback. The impact is direct — reliable, auditable AI that reduces manual effort and raises the quality and speed of everyday decisions across the business.
 

What you will do:

• Design and build production-grade AI workflows that integrate across internal systems (HR, Finance, Operations, CRM).

• Implement the orchestration logic — triggers, retries, fallbacks, and human-in-the-loop patterns — so workflows run reliably, observably, and auditably.

• Develop and maintain the AI agents, prompts, retrieval pipelines, and decision logic that power those workflows.

• Own model behaviour in production: accuracy and usefulness, failure modes, and edge-case and ambiguity handling.

• Iterate on model performance using evaluation frameworks, feedback loops, and real-world usage data.

• Take accountability for decision quality and outcomes — not just technical execution — defining and tracking success metrics such as accuracy, resolution rate, and time saved.

• Diagnose cases where systems are technically “working” but producing poor outcomes, and close the gap.

• Partner with Data Engineering on shared platforms (infrastructure, CI/CD, data pipelines, security and governance) and contribute to shared standards, schemas, and best practices for AI systems.

Who you are:

• Strong software engineering background (Python or similar), with a track record of building production systems — not just prototypes.

• Hands-on experience with AI / ML systems (LLMs, classifiers, decision models, or similar).

• Experience integrating APIs and working with distributed systems.

• Experience designing prompts, retrieval pipelines, or ML inference workflows.

• Solid understanding of model evaluation, monitoring, and feedback loops; comfortable working with both structured and unstructured data.

• Product-oriented — cares about outcomes, not just shipping code; pragmatic about AI and focused on what works in production.

• Comfortable owning ambiguity and making trade-offs.

• Languages: [Add languages required].

• A plus, but not required: workflow orchestration tools (Temporal, Airflow, Step Functions); experience building internal tools or agents; familiarity with regulated or enterprise environments; exposure to MLOps or AI evaluation frameworks.

Why Planet

Planet is an equal opportunity employer where diversity is valued, and all employment is decided based on qualifications, merit, and business need.

Come and grow your career in the most exciting, fast paced technology market, with a business that delivers feel-good connected commerce. We would love to hear from you – Apply now.

At Planet, we embrace a hybrid work model, with three days a week in the office.
 

Reasonable accommodations may be made in order to allow for an individual to perform the essential functions of this role successfully.

Skills Required

  • Strong software engineering background with experience building production systems (Python or similar)
  • Hands-on experience with AI/ML systems (LLMs, classifiers, decision models)
  • Experience integrating APIs and working with distributed systems
  • Experience designing prompts, retrieval pipelines, or ML inference workflows
  • Solid understanding of model evaluation, monitoring, and feedback loops; working with structured and unstructured data
  • Workflow orchestration tools (Temporal, Airflow, Step Functions)
  • Experience building internal tools or agents
  • Familiarity with regulated or enterprise environments
  • Exposure to MLOps or AI evaluation frameworks

Planet (weareplanet.com) Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Planet (weareplanet.com) and has not been reviewed or approved by Planet (weareplanet.com).

  • Fair & Transparent Compensation Company materials indicate salaries are benchmarked to market throughout the year, suggesting a structured approach to aligning pay with role value. Feedback suggests some roles can negotiate competitive offers at hire.

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The Company
HQ: San Francisco, CA
2,648 Employees
Year Founded: 1985

What We Do

Planet is a leading global provider of integrated technology and payments solutions for retail and hospitality customers. We create great experiences for the millions of people who use our Payments, Software, and Tax Free solutions every minute of every day. Planet empowers its customers to deliver amazing customer experiences by combining payments and technology in ways that drive greater loyalty, increase revenue and save time. Founded over 35 years ago and with our headquarters in London, today we have more than 2,500 employees located across six continents serving our customers in over 120 markets

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