Lead GenAI Cloud Developer at Elastic

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. What is The Role At Elastic, we don’t just connect dots; we power the future of work. As the creators of Elasticsearch, Kibana, and Logstash, we are uniquely positioned to turn vast data into actionable intelligence. We are looking for a visionary Lead GenAI Cloud Developer to spearhead the evolution of ElasticGPT—transforming it from a conversational assistant into a proactive, task-oriented agentic ecosystem that removes friction from every Elastician's day. Your Mission: From Chat to Action You will lead the IT GenAI roadmap, moving beyond simple chat interfaces to build intuitive, action-oriented agentic workflows. Your goal is to mature our internal GPT tool’s (ElasticGPT) capabilities so it doesn't just answer questions—it executes tasks, automates complex processes, and serves as the primary driver of workforce productivity. This role requires experience building and operating real-world GenAI systems under constraints of scale, cost, latency, and enterprise governance—not just prototype or experimental workflows. What You Will Be Doing • AI Agent Strategy & Development: Lead the evolution of ElasticGPT into a task-oriented agent. Design sophisticated workflows (both agentic and deterministic) using LangGraph/LangChain/Elastic Agent Builder/n8n (or equivalent frameworks) to automate enterprise-wide productivity. • Production RAG & Retrieval: Architect hybrid retrieval systems (BM25, vector search, RRF) using ESRE and Jina AI. Build data ingestion pipelines across Confluence, Jira, GitHub, and ServiceNow to improve answer quality. • Infrastructure & MLOps: Oversee the full model lifecycle—from fine-tuning to deploying scalable APIs on Kubernetes—across major cloud providers (AWS, Azure, GCP). • Optimization & Observability: Own token efficiency, latency, and cost management. Implement end-to-end tracing (OpenTelemetry) and evaluation pipelines to measure performance. • Multi-Model Orchestration: Design and operate LLM gateway architectures for routing, fallback, spend control, and governance across multiple model providers. • Protocol & Tool Architecture: Define multi-agent patterns, state management, tool contracts, and handoff logic for enterprise workflows. Demonstrate working knowledge of MCPs and modern agent tool-discovery patterns. • Governance & Reliability: Design robust agents with retries, scoped permissions, and audit trails to ensure secure, reliable execution in a business tech stack. What You Bring • Advanced Agentic Expertise: Proven track record of building production-grade agents and RAG systems using frameworks like LangGraph/LangSmith. • Technical Proficiency: Mastery of Python and TypeScript; deep experience with PyTorch, TensorFlow, or Hugging Face. • Elasticsearch Mastery: Deep knowledge of ESRE, vector indexing (HNSW), and relevance tuning. • System Design Intuition: Strong ability to balance the trade-offs between latency, cost, and response quality across multi-model environments (OpenAI, Anthropic, Vertex AI). • Cloud & Scaling: Extensive experience with Kubernetes and managing high-concurrency cloud infrastructure. • Strategic Ownership: A "builder" mindset with the ability to translate complex business needs into technical roadmaps and influence senior stakeholders. • Education & Qualifications • Bachelor's or Master's degree in Computer Science, Engineering, or a related field. • Proven experience in developing generative AI models, including Natural Language Processing (NLP) or computer vision models. • Proficiency in deep learning frameworks such as Microsoft Cognitive Services, TensorFlow, PyTorch, or Hugging Face Transformers. • Strong knowledge of cloud platforms and services (e.g., AWS, Azure, GCP). • Experience with containerization and orchestration (e.g., Docker, Kubernetes). • Knowledge of DevOps practices for model deployment and automation. • Strong problem-solving skills and the ability to work in a dynamic and fast-paced environment. • Excellent communication and collaboration skills. • A commitment to Ethical AI and responsible development practices. #LI-JM5 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 USDThe 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 [Upgrade to PRO to see contact]. We will reply to your request within 24 business hours of submission. 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