Sr. AI Engineer, Application Engineering

Elastic Elastic · Enterprise · United States · IT

This role focuses on the end-to-end technical delivery and development of AI solutions, specifically AI agentic deployments and LLM-based intelligent agents using the Elastic Agent Builder platform. It involves designing, implementing, and orchestrating these systems, with a strong emphasis on custom agent engineering and data integration within enterprise environments.

What you'd actually do

  1. Own the end-to-end technical delivery of AI solutions, including writing code, configuring systems, and resolving issues, while reviewing the work of junior team members to ensure quality deployment and measurable business impact.
  2. Take ownership of designing and implementing scalable production systems, including AI and Large Language Model (LLM) based intelligent agents and automated workflows built on the Salesforce platform.
  3. Work directly with stakeholders to design and build custom intelligent agents using the Elastic Agent Builder platform, ensuring solutions meet unique business requirements and integrate smoothly with existing tool ecosystems.
  4. Own the full data lifecycle, from data model design to building efficient processing pipelines and establishing integration strategies. Ensure data is optimized and secure for AI applications, including in complex enterprise environments.
  5. Identify, analyze, and resolve technical challenges across all phases of solution delivery, from data integration to model deployment and agent orchestration.

Skills

Required

  • At least 5 years' experience in a hands-on, end-to-end delivery role for scalable production solutions in a professional environment
  • Expert-level proficiency in one or more programming languages (e.g., JavaScript, Java, Python)
  • Extensive experience building and deploying solutions with AI/LLM technologies, including integrating LLMs, applying AI orchestration frameworks (e.g., LangChain, LlamaIndex), prompt engineering techniques, and agentic frameworks
  • Deep expertise in data modeling, processing, integration, and analytics, with proficiency in enterprise data platforms (e.g., Salesforce Data Cloud, Snowflake, Databricks, BigQuery)
  • Strong collaboration, communication, and presentation skills, both written and verbal, with the ability to explain complex technical concepts to technical and non-technical partners
  • Track record of leading technical engagements, mentoring junior team members, and taking responsibility for technical aspects of projects

Nice to have

  • Experience developing and deploying conversational AI solutions
  • Expert-level experience with Python in a professional setting
  • Prior experience in a solution engineering or technical lead role
  • Experience contributing to open-source AI frameworks or libraries

What the JD emphasized

  • AI agentic deployments
  • AI Agent Builder platform
  • LLM based intelligent agents
  • automated workflows
  • custom intelligent agents
  • agent orchestration

Other signals

  • AI agentic deployments
  • AI Agent Builder platform
  • LLM based intelligent agents
  • automated workflows
  • custom intelligent agents
  • agent orchestration