AI Engineer

AI Engineer – Performance Management

Experience: 2–3 years Function: AI Engineering / Performance Management Industry: Oil & Gas

About The Role

Working with a major oil and gas company to deliver a portfolio of AI initiatives focused on project and performance management. We are looking for an AI Engineer who will design and build a bespoke project and performance management tools from the ground up, leveraging enterprise AI tools and state-of-the-art LLMs to transform how the business measures, analyzes, and improves operational performance on major projects.

This role is ideal for an engineer who is genuinely passionate about generative AI, who keeps a close pulse on the rapidly evolving AI tooling landscape, and who is excited to apply that knowledge in a high-impact, real-world enterprise context.

Key Responsibilities

Design, develop, and deploy enterprise CoPilot agents and workflows for members of the team to improve their productivity and decision-making
Design, develop, and deploy a bespoke an AI-powered performance management tool tailored to the client's operational and organizational needs.
Build LLM-driven workflows using enterprise AI systems,, Claude, Claude Code, and other leading models (e.g., ChatGPT, Gemini, open-source frontier models) to automate analysis, reporting, and decision support.
Integrate the tool with existing enterprise data sources (Data systems, SharePoint, Excel-based KPI trackers).
Develop and refine prompts, agentic workflows, and retrieval pipelines (RAG) to deliver accurate, context-aware insights to business users.
Act as a productivity coach for members of the team and teach an enthusiastic team how to get the most out of AI.
Translate business and operational performance requirements into robust, production-grade AI features.
Continuously evaluate and benchmark new models, frameworks, and tools, and recommend adoption where they add measurable value.
Partner with performance management leads, data teams, and end users to gather feedback and iterate quickly.
Ensure responsible AI practices including data privacy, security, hallucination mitigation, and clear human-in-the-loop controls — particularly important in a regulated oil & gas environment.

Required Qualifications & Experience

2–3 years of professional experience in AI, machine learning, data science, or software engineering, with hands-on exposure to LLM-based applications.
Practical experience building applications with modern LLMs and the Microsoft enterprise environment with CoPilot (Claude, ChatGPT, Llama, Gemini, or similar) including prompting, function calling/tool use, and agentic patterns.
Hands-on experience with Claude Code or comparable AI coding assistants for building production tools.
Strong programming skills in Python; familiarity with TypeScript/JavaScript a plus.
Experience with RAG pipelines, vector databases and orchestration frameworks
Comfortable working with APIs, cloud platforms (AWS, Azure), and integrating with enterprise data systems.
Excellent communication skills, with the ability to translate technical concepts for non-technical business stakeholders.
Genuine enthusiasm for AI — actively follows new tools, papers, and product releases, and can speak credibly about what's changed in the last 30–90 days.
Experience deploying AI solutions in enterprise environments with strict security and compliance requirements.
Front-end skills (React, Next.js) for building user-facing AI tools.
Experience with MCP (Model Context Protocol) servers and connector-based architecture.

Key Skills

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