Applied AI Engineer

Praecipio

• $120K — $145K *
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
  • A minimum of seven years building a software engineering foundation, successful candidates will have a strong software engineering background.
  • Technical Disciplines: Proficiency in core technical disciplines that have become essential for AI best practices:
    • DevOps
    • Quality Assurance (QA)
    • Linux/Unix System Administration (specifically, being comfortable in a non-Windows environment)
  • API Proficiency: Demonstrated understanding of APIs, including REST, SOAP, and other forms of interaction.
  • A minimum of two years of experience in Extract, Transform, and Load (ETL) processes or similar data platform work.
  • Git Platform Proficiency: Ability to work with Git platforms (e.g., GitHub, GitLab, Bitbucket) and manage repositories.
  • Coding Agent Experience: Proven ability to successfully create software using coding agents (e.g., Claude Code, Codex) rather than just manual coding.
  • Project Maintenance: Demonstrated experience maintaining ongoing software projects rather than just building one-off applications, including experience collaborating with other contributors.
  • Client-Facing/Professional Services: Experience in professional services or client-facing roles, with a focus on bleeding-edge technology rather than outdated playbooks.


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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