The demand for AI Engineers in cybersecurity is growing rapidly, especially as organizations face more advanced and AI-driven cyber threats. The StoneX AI Engineer role offers a unique opportunity for freshers and early-career professionals to work at the intersection of Artificial Intelligence, cybersecurity, and agent-based systems.
This role is not just about building models it’s about developing intelligent AI agents that can detect, analyze, and respond to real-world threats in real time. If you are passionate about LLMs, RAG systems, and security applications of AI, this opportunity can significantly accelerate your career.
About the Company
StoneX Group Inc. is a global financial services organization that provides institutional-grade tools, platforms, and services across trading, risk management, and financial operations.
With the rapid evolution of cyber threats in 2026, StoneX is investing heavily in AI-powered cybersecurity systems. Their Detection Engineering team is focused on building next-generation threat detection solutions using autonomous AI agents, making it an exciting place for engineers interested in real-world AI applications.
Role Overview
As an AI Engineer at StoneX, you will be part of the Detection Engineering team, working on building intelligent systems that automate cybersecurity workflows.
This role focuses on:
- AI agent development
- Cybersecurity use-case engineering
- Real-time threat detection
You will collaborate with security engineers, threat hunters, and SOC teams to build systems that improve detection accuracy, reduce false positives, and enhance overall security operations.
Key Responsibilities
- Collaborate with security teams to identify and design AI agent use cases
- Build production-grade AI agents using LLM frameworks
- Develop RAG (Retrieval-Augmented Generation) systems for contextual threat analysis
- Work on prompt engineering, tool integration, and agent workflows
- Integrate AI solutions into SIEM/XDR and security platforms
- Assist in data preparation, feature engineering, and model tuning
- Monitor and improve agent performance (accuracy, cost, drift)
- Document architectures, workflows, and operational playbooks
- Stay updated with advancements in AI and cybersecurity
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Who Can Apply
| Criteria | Details |
|---|---|
| Education | Bachelor’s in CS, Cybersecurity, Data Science, or related field |
| Experience | 0–2 Years |
| Skills | AI/ML, LLMs, RAG, Python (preferred) |
| Tools | Git, data systems, basic cloud knowledge |
| Soft Skills | Problem-solving, communication |
Preferred Skills
- Experience with AI agents or LLM-based applications
- Knowledge of RAG, prompt engineering, and tool-calling
- Familiarity with cybersecurity tools like SIEM, XDR, or EDR
- Understanding of MITRE ATT&CK framework
- Exposure to cloud platforms (AWS, Azure, or GCP)
- Basic understanding of MLOps or AgentOps practices
- Projects or contributions in AI, cybersecurity, or automation
What You’ll Get
- Hands-on experience with real-world AI-powered cybersecurity systems
- Opportunity to work on agentic AI and LLM-based architectures
- Exposure to enterprise-scale security environments
- Collaboration with experienced engineers and security experts
- Career growth in one of the fastest-growing tech domains
- Learning opportunities in both AI and cybersecurity domains
Stipend / Salary (Market Estimate) 💰
StoneX has not officially disclosed the salary for this entry-level role. However, based on industry standards for AI Engineer (0–2 years) roles in Bangalore, the estimated compensation is:
👉 ₹6 LPA – ₹12 LPA
This can vary depending on:
- Candidate skill level (LLMs, RAG, AI agents)
- Internship/project experience
- Knowledge of cybersecurity and cloud systems
Candidates with strong hands-on projects in AI agents, RAG systems, or security tools may receive higher offers.
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Why You Should Apply
This role is particularly valuable because it sits at the intersection of three high-demand domains:
- Artificial Intelligence (LLMs, RAG, Agentic AI)
- Cybersecurity
- Cloud & Data Systems
Instead of working on isolated ML models, you will build production-ready AI systems that directly impact security operations. This gives you exposure to real-world complexity, which is highly valued in the industry.
Additionally, working on agent-based AI systems and security use cases can open doors to advanced roles such as:
- AI Security Engineer
- LLM Engineer
- Threat Intelligence Engineer
- ML Platform Engineer
How to Apply
To apply for the StoneX AI Engineer role, follow these steps:
- Prepare a strong resume highlighting:
- AI/ML projects (especially LLMs, RAG, or agents)
- Any cybersecurity-related experience
- Programming skills (Python, APIs, etc.)
- Showcase practical work:
- GitHub projects (AI agents, chatbots, automation tools)
- Mini projects involving data pipelines or security logs
- Focus on fundamentals:
- Machine Learning basics
- Prompt engineering and LLM workflows
- Problem-solving skills
- Apply by clicking the apply button below and completing the application form.
Before applying, make sure your resume reflects real, hands-on experience, even if it comes from personal or academic projects.
Disclaimer: This job information is collected from official or publicly available sources. We do not charge any fees for job information and do not guarantee recruitment. Applicants are advised to verify details from the official company website. We are not responsible for any loss arising from reliance on this information.
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