Lead GenAI Cloud Developer

Elastic

1d • $101,900 - $151,900 • Remote

About The Position

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 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.

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.

Requirements

• Proven track record of building production-grade agents and RAG systems using frameworks like LangGraph/LangSmith.
• Mastery of Python and TypeScript; deep experience with PyTorch, TensorFlow, or Hugging Face.
• Deep knowledge of ESRE, vector indexing (HNSW), and relevance tuning.
• Strong ability to balance the trade-offs between latency, cost, and response quality across multi-model environments (OpenAI, Anthropic, Vertex AI).
• Extensive experience with Kubernetes and managing high-concurrency cloud infrastructure.
• A "builder" mindset with the ability to translate complex business needs into technical roadmaps and influence senior stakeholders.
• 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.

Responsibilities

• 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.
• 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.
• Oversee the full model lifecycle—from fine-tuning to deploying scalable APIs on Kubernetes—across major cloud providers (AWS, Azure, GCP).
• Own token efficiency, latency, and cost management.
• Implement end-to-end tracing (OpenTelemetry) and evaluation pipelines to measure performance.
• Design and operate LLM gateway architectures for routing, fallback, spend control, and governance across multiple model providers.
• 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.
• Design robust agents with retries, scoped permissions, and audit trails to ensure secure, reliable execution in a business tech stack.

Benefits

• Company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings
• Stock program eligibility
• Competitive pay based on the work you do here and not your previous salary
• Health coverage for you and your family in many locations
• Flexible locations and schedules
• Generous number of vacation days each year
• Up to $2000 (or local currency equivalent) match for financial donations and service
• Up to 40 hours each year to use toward volunteer projects
• Minimum of 16 weeks of parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior