Elastic AI Engineer

Role Overview The Elastic IT team is moving beyond simple chat to the next frontier: Agentic Workflows. We are looking for an innovative Elastic AI Engineer to build autonomous, enterprise-grounded agents that go beyond answering questions and actually complete complex business tasks to accelerate productivity across the organization. What You Will Be Doing - Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes. - Apply Retrieval Augmented Generation (RAG) and the Elasticsearch Relevance Engine (ESRE) to ensure agents are deeply grounded in enterprise knowledge for high-accuracy task completion. - Develop and fine-tune large language models and integrate them with internal APIs and third-party SaaS tools to enable autonomous action. - Build a scalable, cloud-based infrastructure (AWS, Azure, GCP) that supports the high-concurrency demands of enterprise agents. - Oversee training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant. - Act as a domain expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity. - Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes. - Implement standards for security and data privacy to protect sensitive information and ensure compliance with relevant regulations. What You Bring - 3-5 years of relevant work experience. - Minimum 1 year of experience building with the Elastic Stack. - Knowledge of Elasticsearch Relevance Engine (ESRE), Jina AI, and advanced RAG patterns. - Proven success delivering independent GenAI projects that involve autonomous task completion or complex workflow automation. - Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems. - Deep familiarity with leading agentic AI and workflow automation platforms such as Microsoft Copilot Studio, Salesforce Agentforce, and ServiceNow AI Agents. - Proven ability to apply emerging market trends (e.g., Multi-Agent Orchestration and Model Context Protocol) to build high-impact, cost-optimized solutions at scale. - Experience with Python or TypeScript for backend logic and agent orchestration. - Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment. - Hands-on experience with LLM providers. Bonus Points - Bachelor's or Master's degree in Computer Science or a related engineering field. - Strong communication skills with the ability to translate business requirements into technical agent architectures. - A commitment to Ethical AI and responsible development practices. - Experience with containerization and orchestration (e.g., Docker, Kubernetes). - Knowledge of DevOps practices for model deployment and automation. Compensation Base salary only. Typical starting salary range: $101,900 - $161,200 CAD. Benefits -