Applied AI Engineer

Praecipio

$110K — $130K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Proficient in Git, GitHub, and Claude Code in the terminal.
  • Proven experience in deploying production-ready agentic or LLM-backed systems.
  • Strong understanding of enterprise tooling and API integration.
  • Effective communication with non-technical audiences in client settings.
  • Demonstrated ability to deliver working prototypes before expanding features.

Responsibilities

  • Design and implement agentic systems for enterprise clients.
  • Develop internal workflows to enhance organizational efficiency.
  • Engage with clients directly to execute advisory projects.
  • Incorporate lessons learned from builds into shared practice methodologies.
  • Collaborate closely with technical and enablement leads for successful system delivery.

Benefits

  • Opportunity to work on real-world AI applications with direct impact.
  • Collaborative environment alongside experienced technical leads.
  • Focus on hands-on building rather than theoretical frameworks.
  • Engagement in a company fully committed to AI-driven solutions.
Full Job Description
Applied AI Engineer

You are a builder. Your deliverable is a running system, not a framework or a strategy deck.

You will work alongside a technical lead who defines the architecture and an enablement lead who drives adoption. Your job is the part in between: making new systems exist.

What You'll Do
  • Design and build agentic systems for enterprise clients: workflow deployments, integrations, and production AI builds
  • Build internal agentic workflows across Praecipio's delivery, sales, and operations functions
  • Support advisory engagements where hands-on execution is required, sitting with clients and shipping alongside them
  • Bring what you learn from every build back into the practice's shared patterns and methodology
What You Bring

Non-negotiable: You work in Git, GitHub, and Claude Code in the terminal today. This is the baseline toolchain for everything we build.
  • Demonstrated ability to ship agentic or LLM-backed systems that run in production, not just demos
  • Fluency with enterprise tooling and APIs; comfort integrating with the systems businesses actually run on
  • Client-facing composure: you can explain what you built and why it matters to a non-technical audience
  • Pragmatism about scope: you ship the working version, then improve it


An Atlassian background is helpful but not required. We hire practitioners for build depth and apply it across our full delivery portfolio, Atlassian engagements included.

Why This Role

Most AI jobs are either research or slideware. This one is shipping: real systems, real users, at a company where AI-native delivery is the whole strategy rather than a side bet.

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