AI Automation Forward Deployment Engineer

What is The Role

We're hiring an AI Forward Deployed Automation Engineer to lead AI agentic deployments and deliver real impact for our customers. This is a great opportunity to work at the intersection of engineering and customer success!

In this role, you'll design and develop tailored solutions using the Elastic Agent Builder platform and related technologies, guide technical engagements, and support the growth of junior engineers. The work spans from concept through deployment, requiring strong problem-solving skills and a collaborative approach to delivering value in complex, real-world environments.

What You Will Be Doing

• Technical Delivery and Implementation
  • 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.
• AI Solution Development
  • 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.
• Custom Agentic AI Engineering
  • 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.
• Data Configuration and Integration
  • 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.
• Technical Problem Solving
  • Identify, analyze, and resolve technical challenges across all phases of solution delivery, from data integration to model deployment and agent orchestration. Serve as a reliable resource for unblocking progress.
• Agentic Innovation
  • Develop expertise in the Elastic platform, pushing its capabilities forward. Lead the development of custom intelligent agents, automate business processes, and shape user experiences. Insights from the field will directly influence product enhancements and platform direction.
• Client Partnership
  • Embed with client teams to understand their operational challenges and goals. Translate requirements into clear technical designs, build strong relationships, and serve as a trusted technical advisor.
• Debugging and Root Cause Analysis
  • Perform thorough analysis, debugging, and root cause identification for complex system interactions, data flows, and AI model behaviors to optimize performance and prevent recurring issues.
• Prototyping and Iteration
  • Rapidly develop proofs-of-concept and minimum viable products, often coding alongside client teams to demonstrate capabilities and gather feedback for iterative refinement.
• Engineering Best Practices
  • Apply and promote standards for code quality, scalability, security, and maintainability across all deployed solutions.

What You Bring

• 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

Bonus Points

• 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