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Agile Fuel | World-class Dedicated Engineering Teams

AI Engineer

Agile Fuel | World-class Dedicated Engineering Teams, Mountain View, California, us, 94039

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Overview The open position is for an

AI Engineer

within the Quantitative Research Platform team at

Agile Fuel | World-class Dedicated Engineering Teams . The role requires strong experience in Python, AWS, and modern AI/ML techniques, particularly in agentic AI systems and prompt engineering. The engineer will work closely with quants, researchers, and traders to design and scale AI-powered infrastructure for trading models, risk analysis, and automated decision-making.

Responsibilities

Design, build, and maintain AI agents to support trading, risk, and research workflows;

Implement LLM-driven prompt engineering for data extraction, transformation, and knowledge integration;

Collaborate with Quant Researchers to translate trading strategies into AI-enabled systems;

Deploy and scale solutions on AWS cloud infrastructure with best practices in performance and security;

Develop pipelines for integrating market, fundamental, and alternative datasets into AI/ML workflows;

Partner with data engineers and software developers to integrate AI models into the Quantitative Research Platform;

Contribute to the development of multi-agent coordination frameworks to support automated decision-making in commodity trading.

Requirements

3–5 years of experience in AI/ML engineering or applied data science;

Strong proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow, LangChain or similar);

Familiarity with MCP (Model Context Protocol) or similar orchestration frameworks;

Experience with AWS (EC2, S3, Lambda, SageMaker, Step Functions, etc.);

Hands-on expertise in agentic AI frameworks, multi-agent systems, or LLM orchestration;

Proficiency in Prompt Engineering for LLMs and workflow optimization;

Understanding of financial markets, quantitative research, or commodities trading (preferably base metals);

Strong software engineering background, including version control (Git), testing, and CI/CD;

At least an Intermediate English level (both spoken and written).

Bonus points

Background in quantitative finance or exposure to commodity trading;

Experience with reinforcement learning, optimization, or simulation frameworks;

Knowledge of data engineering workflows (ETL pipelines, data lakes, APIs);

Previous work in high-frequency or systematic trading environments.

Benefits

People-oriented management without bureaucracy;

Flexible schedule;

25 working days of annual paid vacation;

Paid sick leaves;

Friendly and engaging professional team;

Opportunities for self-realization, career, and professional growth;

Accounting and legal support.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

IT Services and IT Consulting

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