AI Developer

Role:
We are seeking an enthusiastic AI Developer to design, implement, and scale intelligent tools that enable smarter decision-making and operational efficiency across the business. You’ll be joining a new, nimble team at the center of a digital transformation effort for a private equity-backed oil and gas firm—where AI is not an experiment, but a core strategy.

This role offers a unique opportunity to shape how AI is used across the enterprise—from building copilots for field operations and finance, to embedding intelligence into internal systems that automate repetitive work and unlock strategic insights.
 
What You’ll Do
•    Enable generative AI functionality on internal applications by designing and integrating LLM-powered features that enhance user workflows.
•    Help build AI-based applications from concept through production, including prototyping, testing, and iterative refinement.
•    Deploy ML solutions to solve operational-technology challenges, collaborating with OT teams to translate data insights into automated controls and predictive maintenance.
•    Collaborate with business stakeholders to identify high-impact automation and AI opportunities across departments.
•    Build, test, and deploy AI-powered components and applications using generative AI and data pre-processing back ends.
•    Create reusable prompt-engineering patterns, chaining logic, and inference pipelines that integrate seamlessly with internal systems.
•    Fine-tune and evaluate open-source and proprietary foundation models using internal datasets.
•    Partner with data engineers and software developers to ingest, structure, and index data from operational systems, documents, and third-party sources.
•    Design lightweight automation workflows using tools such as n8n to connect AI components with business processes.
•    Ensure AI applications meet standards for security, performance, and explainability—and deliver consistent business value.
 

What You’ll Need
•    Proficient in Python, with the ability to write, test, and maintain reusable code.
•    Experience with LangChain or LlamaIndex, and working knowledge of prompt chaining and orchestration patterns.
•    Strong understanding of LLMs, embeddings, vector databases (e.g., Pinecone, Supabase), and RAG architecture and the ability to implement necessary data structures. 
•    Hands-on experience in prompt engineering and deploying AI agents or assistants into user-facing workflows.
•    Ability to evaluate model performance, refine prompts, and iterate quickly on solution design.
•    Comfortable working with REST APIs, structured and unstructured data, and integrating diverse data sources into model pipelines.
•    Working knowledge of SQL, Azure Blob Storage, or Azure Data Lake for handling enterprise datasets.
•    Experience deploying solutions on cloud-native infrastructure—ideally Azure Functions, Docker, and FastAPI.
•    Familiar with CI/CD pipelines, Git-based workflows, and basic monitoring for deployed AI services.
•    Ability to translate business needs into technical implementations and explain AI-driven results in clear, business-friendly language.
•    Familiarity with workflow automation and low-code tools like n8n, Retool, or Power Platform for quickly assembling operational flows and interfaces.
•    Experience with Python, LangChain, LlamaIndex, Azure ML, Hugging Face, REST APIs, Azure Functions, and major LLMs such as OpenAI/Anthropic.
•    Bachelor’s degree in Computer Science, Data Science, AI, or equivalent practical experience.
•    2–3 years of hands-on experience (internships, projects, coursework) applying AI or NLP techniques.