Elastic - AI Engineer
Requirements
• 3-5 years of work experience in a relevant field. • Minimum 1 year experience building with the Elastic Stack. • Knowledge of Elasticsearch Relevance Engine (ESRE), Jina AI, and advanced RAG patterns is critical. • Proven success in delivering independent GenAI projects, specifically those involving autonomous task completion or complex workflow automation. • Proven success • Agentic Frameworks: Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems. • Agentic Frameworks: • LangGraph • LangChain • LangSmith • Expertise in Enterprise Agentic & Workflow Platforms: Deep familiarity with leading agentic AI and workflow automation platforms (such as Microsoft Copilot Studio, Salesforce Agentforce, ServiceNow AI Agents.) • Expertise in Enterprise Agentic & Workflow Platforms: • Market Trend Integration: Proven ability to apply emerging market trends—such as Multi-Agent Orchestration and Model Context Protocol (MCP)—to build high-impact, cost-optimized solutions that scale across the enterprise. • Market Trend Integration: • Multi-Agent Orchestration and • Model Context Protocol (MCP) • Programming: Experience with Python or TypeScript for backend logic and agent orchestration. • Programming: • Python • TypeScript • Cloud & Orchestration: Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment. • Cloud & Orchestration: • Kubernetes • Docker • Terraform • Model Expertise: Hands-on experience with LLM providers. • Model Expertise: • 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. • Ethical AI • Experience with containerization and orchestration (e.g., Docker, Kubernetes). • Knowledge of DevOps practices for model deployment and automation. • Additional Information - We Take Care of Our People: • As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do. • We strive to have parity of benefits across regions, and while regulations differ from place to place, we believe taking care of our people is the right thing to do. • Competitive pay based on the work you do here and not your previous salary • Health coverage for you and your family in many locations • Ability to craft your calendar with flexible locations and schedules for many roles • Generous number of vacation days each year • Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service • Up to 40 hours each year to use toward volunteer projects you love • Embracing parenthood with a minimum of 16 weeks of parental leave
Responsibilities
• Agentic Strategy & Design: Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes. • Agentic Strategy & Design: • Enterprise Grounding: 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. • Enterprise Grounding: • AI Model & Tool Integration: Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action. • AI Model & Tool Integration: • Scalable Infrastructure: Firm understanding of cloud-based environments (AWS, Azure, GCP) in order to support the high-concurrency demands of enterprise agents. • Scalable Infrastructure: • Lifecycle Management: Oversee the training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant. • Lifecycle Management: • Technical Leadership: Act as a domain expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity. • Technical Leadership: • Documentation: Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes. • Documentation: • Security: Implement standards for security and data privacy to protect sensitive information and ensure compliance with relevant regulations. • Security:
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