Agentic AI Engineer — Build Autonomous Workflows (Hybrid)

Fervo Energy Co.; Colorado; Hybrid; USD 103,000 - 159,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

Paid time off

Parental leave

Stock options

Bonus incentive

401(k) match

Job summary

Fervo Energy is seeking an Agentic AI Engineer to design and ship agentic workflows that convert unstructured knowledge and operational data into autonomous capabilities for engineers, operators, and decision-makers in the field.

The role owns end-to-end delivery from framing and architecture to prototyping, deployment, and iteration in production, collaborating with Data Engineering, IT Infrastructure, and domain SMEs to establish reusable patterns for retrieval, grounding, and agent

Qualifications

• Bachelor’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.
• Strong Python skills, including async patterns, API design with FastAPI, and writing testable production code.
• Demonstrated experience with LangChain/LangGraph, LlamaIndex, AutoGen, or Semantic Kernel.
• Working knowledge of LLM APIs and SDKs (OpenAI, Azure OpenAI), including tool use, structured outputs, and prompt engineering.
• Experience implementing RAG architectures with vector databases and embedding models.
• Experience with agent orchestration patterns including multi-step planning and tool routing.

Responsibilities

• Design and deploy end-to-end agentic AI workflows using planner–worker, orchestrator–executor, multi-agent, and RAG-based architectures.
• Build reusable components and reference patterns for tool routing, state management, error handling, and human-in-the-loop checkpoints.
• Implement robust retrieval pipelines (hybrid search, vector + keyword) over technical documents, historian data, and operational records.
• Translate domain problems from drilling, completions, production, geophysics, and plant operations into well-scoped agentic use cases with clear success metrics.
• Establish agent evaluation frameworks including golden datasets, automated regression tests, and structured evals for accuracy, faithfulness, and tool-use correctness.
• Implement tracing, logging, and observability across agent runs to support debugging, cost monitoring, and continuous improvement.
• Build feedback loops that capture user input and convert it into eval cases and prompt/system improvements.
• Support production incidents and platform-level issues impacting deployed agents.
• Deploy agents as production services on Azure-native stack with Entra ID SSO, Key Vault, and cost controls.
• Lead design reviews and cross-functional enablement sessions on agentic AI patterns and best practices.

Skills

Python

Async patterns

FastAPI

LangChain/LangGraph

LLM tooling

Version control

CI/CD

Docker

Terraform

Observability

Production ops

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

Azure OpenAI

OpenAI

LangChain

LangGraph

LlamaIndex

AutoGen

Semantic Kernel

Databricks

Snowflake

dbt Semantic Layer

Neo4j

Chroma

PGVector

Job description

Fervo Energy is seeking an Agentic AI Engineer to design and ship agentic workflows that convert unstructured knowledge and operational data into autonomous capabilities for engineers, operators, and decision-makers in the field.

The role owns end-to-end delivery from framing and architecture to prototyping, deployment, and iteration in production, collaborating with Data Engineering, IT Infrastructure, and domain SMEs to establish reusable patterns for retrieval, grounding, and agent