Agentic AI Engineer

Hybrid Remote • Houston, TX • Data Science Job TypeFull-timeDescriptionFervo is building the most cost-effective, repeatable geothermal power plants in the world. Scaling that mission requires AI-native capabilities that drive measurable impact across drilling, completions, production, geophysics, and power plant operations. The Agentic AI Engineer, within the Data & AI team, designs and ships agentic workflows that turn unstructured knowledge and structured operational data into autonomous capabilities for engineers, operators, and decision-makers in the field.The Agentic AI Engineer owns the end-to-end delivery of agentic AI use cases — from problem framing and architecture, through prototyping, evaluation, deployment, and iteration in production. Working across Data Engineering, IT Infrastructure, domain SMEs, and business stakeholders, this role establishes reusable patterns for retrieval, semantic grounding, tool integration, and agent orchestration on top of our Azure, Databricks, and Snowflake stack. Success requires strong hands-on engineering depth, sound architectural judgment, and pragmatism about what to ship versus what to defer.RequirementsResponsibilitiesAgentic Workflow Design & DeliveryDesign and deploy end-to-end agentic AI workflows using planner–worker, orchestrator–executor, multi-agent, and RAG-based architecturesBuild reusable components and reference patterns for tool routing, state management, error handling, and human-in-the-loop checkpointsImplement robust retrieval pipelines (hybrid search, vector + keyword, graph-aware retrieval) over technical documents, historian data, and operational recordsTranslate domain problems from drilling, completions, production, geophysics, and power plant operations into well-scoped agentic use cases with clear success metricsSemantic Grounding & Knowledge IntegrationBuild and maintain a semantic layer over our data lake and warehouse using Snowflake Semantic Views and Databricks Unity Catalog Metric Views, making business concepts queryable by both humans and agentsDevelop and curate knowledge graphs that connect domain entities (wells, pads, assets, equipment, events, documents) and serve as grounding context for LLM reasoningStandardize how agents access enterprise data through Model Context Protocol (MCP) servers and equivalent integration patternsEvaluation, Observability & Production OperationsEstablish agent evaluation frameworks including golden datasets, automated regression tests, and structured evals for accuracy, faithfulness, and tool-use correctnessImplement tracing, logging, and observability across agent runs to support debugging, cost monitoring, and continuous improvementBuild feedback loops that capture user input and convert it into eval cases and prompt/system improvementsSupport production incidents and platform-level issues impacting deployed agentsDeployment & EnablementDeploy agents as production services on our Azure-native stack (App Service, Container Apps, Functions) with Entra ID SSO, Key Vault-managed secrets, and proper cost controlsBuild lightweight UIs (Streamlit, Gradio, or React) for agentic applications and internal toolsLead design reviews and cross-functional enablement sessions on agentic AI patterns and best practicesQualificationsRequiredBachelor's or Master's degree in Computer Engineering or Data Science preferred. 2+ years of hands-on experience building and deploying agentic AI or LLM-powered applications in production, not just prototypes or notebooksStrong Python skills, including async patterns, API design with FastAPI, and writing testable, maintainable production codeDemonstrated experience with at least one major agent framework: LangChain/LangGraph, LlamaIndex, AutoGen, or Semantic KernelWorking knowledge of LLM APIs and SDKs (Anthropic Claude, OpenAI, Azure OpenAI), including tool use/function calling, structured outputs, streaming, and prompt engineeringExperience implementing RAG architectures with vector databases (Azure AI Search, pgvector, Pinecone, Weaviate, Chroma, or similar) and embedding modelsExperience with agent orchestration patterns including multi-step planning, tool routing, state management, and graceful failure handlingFamiliarity with Model Context Protocol (MCP) or equivalent standards for tool and context integrationCloud deployment experience on Azure (App Service, Container Apps, Functions, Key Vault, Entra ID), or equivalent in AWS/GCP with willingness to work in our Azure-first environmentStrong Git and CI/CD experience, including version control discipline, code review, and automated testingExperience with containerization (Docker) and infrastructure-as-code (Terraform preferred)Strong observability and production operations skills, including structured logging, tracing, cost monitoring, and runbook developmentPreferredExperience designing or working with semantic models and semantic layers — Snowflake Semantic Views, Databricks Metric Views, dbt Semantic Layer, Cube, or Power BI semantic modelsHands-on experience with knowledge graphs: graph databases (Neo4j, Azure Cosmos DB Gremlin), RDF/SPARQL, ontology design, or graph-augmented RAGExperience with agent evaluation tooling such as LangSmithExperience with our broader data stack: Databricks, Snowflake, Azure Data Lake Storage (ADLS), Azure Data FactoryOil and gas or energy industry experience, including familiarity with drilling, completions, production, geophysics, or industrial historian dataBackground in time-series data, signal processing, or industrial IoT (MQTT, OPC UA, SparkplugB)Experience with multimodal models for handling well logs, schematics, or scanned reports LocationFervo Energy is headquartered in Houston, TX, with growing offices in Golden, CO, Reno, NV, and Oakland, CA, and Salt Lake City, UT. This position will be eligible for some hybrid work flexibility, but regular in-office presence at the Golden or Houston office will be required.Compensation & BenefitsFervo provides a comprehensive suite of benefits including medical, dental, vision, life, short-term and long-term disability, flexible paid time off, and paid parental leave. Additionally, Fervo offers an incentive stock options program, a bonus incentive program, and a 401(k) plan with an employer match.Fervo Energy is providing the compensation range and general description of other compensation and benefits that the company in good faith believes it might pay and/or offer for this position based on the successful applicant’s education, experience, knowledge, skills, and abilities in addition to internal equity and geographic location. Expected Salary: $103,152 - $158,588 based on location and experience.Fervo Energy reserves the right to ultimately pay more or less than the posted range and offer other compensation, depending on circumstances not related to an applicant’s sex or other status protected by local, state, or federal law.