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Elastic

Elastic AI Engineer

Posted 24 Days Ago
Remote
Hiring Remotely in United States
94K-149K Annually
Mid level
Remote
Hiring Remotely in United States
94K-149K Annually
Mid level
Design and build autonomous, enterprise-grounded AI agents and workflows using the Elastic Stack, RAG, and LLMs. Integrate models with internal APIs and SaaS, manage deployment and scaling on cloud/Kubernetes, ensure security/compliance, document systems, and provide technical leadership for agent lifecycle and performance optimization.
The summary above was generated by AI

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

At Elastic, we have a simple goal: to solve the world's data problems with products that delight and inspire. As the company behind the popular open-source projects — Elasticsearch, Kibana, Logstash, and Beats — we help people around the world do great things with their data. From stock quotes to Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots. The Elastic family unites employees across 40+ countries into one coherent team, while the broader community spans across over 100 countries.

What is The Role

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 join our team to build autonomous, enterprise-grounded agents that don't just answer questions—they complete complex business tasks to accelerate productivity across the entire organization.

The ideal candidate is an Elastic product expert (including but not limited to Agent Builder and Workflows), using the full power of the Elastic Stack to provide the "brain" and "memory" for our agentic ecosystem.

Are you ready to build the agents that supercharge enterprise efficiency? Join us to enable agentic workflows that turn collective knowledge into instant action, empowering everyone at Elastic to achieve more. 

What You Will Be Doing:
  • Agentic Strategy & Design: Invent and implement sophisticated agentic workflows that use reasoning and tools to complete end-to-end business processes.
  • 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.
  • AI Model & Tool Integration: Develop and fine-tune LLMs and integrate them with internal APIs and third-party SaaS tools to enable autonomous action.
  • Scalable Infrastructure: Firm understanding of cloud-based environments (AWS, Azure, GCP) in order to support the high-concurrency demands of enterprise agents.
  • Lifecycle Management: Oversee the training, deployment, and performance optimization of agents, ensuring they remain secure, reliable, and compliant.
  • Technical Leadership: Act as a domain expert on the Elastic Stack, making technical recommendations that push the boundaries of AI-driven productivity.
  • Documentation: Maintain comprehensive documentation of AI workflows, cloud infrastructure, and deployment processes.
  • Security: Implement standards for security and data privacy to protect sensitive information and ensure compliance with relevant regulations.
What you bring:
  • 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.
  • Agentic Frameworks: Familiarity with LangGraph, LangChain, and LangSmith for building and debugging multi-agent systems.
  • 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.)
  • 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.
  • Programming: Experience with Python or TypeScript for backend logic and agent orchestration.
  • Cloud & Orchestration: Familiarity with Kubernetes (Operators/Controllers), Docker, and Terraform for automated deployment.
  • Model Expertise: 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 for this role is in the form of base salary.  This role does not have a variable compensation component.  

The typical starting salary range for new hires in this role is listed below.  In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below. 

These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting.  We may ultimately pay more or less than the posted range, and the ranges may be modified in the future.  

An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.

Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program.  Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.

The typical starting salary range for this role is:
$94,300$149,200 USD
The typical starting salary range for this role in the select locations listed above is:
$113,300$179,200 USD
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 minimum of 16 weeks of parental leave

Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.

We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email [email protected]. We will reply to your request within 24 business hours of submission.

Applicants have rights under Federal Employment Laws, view posters linked below: Family and Medical Leave Act (FMLA) Poster; Pay Transparency Nondiscrimination Provision Poster; Employee Polygraph Protection Act (EPPA) Poster and Know Your Rights (Poster)

Elasticsearch develops and distributes technology and information that is subject to U.S. and other countries’ export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic.

Please see here for our Privacy Statement.

Top Skills

Agent Builder
AWS
Azure
Beats
Docker
Elasticsearch
Elasticsearch Relevance Engine (Esre)
GCP
Jina Ai
Kibana
Kubernetes
Langchain
Langgraph
Langsmith
Llm Providers
Logstash
Microsoft Copilot Studio
Model Context Protocol (Mcp)
Multi-Agent Orchestration
Python
Retrieval Augmented Generation (Rag)
Salesforce Agentforce
Servicenow Ai Agents
Terraform
Typescript
Workflows

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