Senior Engineer (Applied Artificial Intelligence)
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 27, 2026.
Join Cboe as a Senior Engineer (Applied Artificial Intelligence) and play a central role in integrating AI into our core operations and developing AI-native products. You will own the full lifecycle of AI initiatives, from scoping and discovery to design, development, and deployment of production-grade systems. This high-ownership, high-impact role requires deep technical expertise and strong communication skills. You will also mentor other engineers on the team and help establish the standard for how we build AI at Cboe.
Missions
- Design, build, and deploy production-ready AI agents and agentic systems across Cboe's internal platforms and workflows.
- Own scoping and discovery for AI initiatives - partnering directly with non-technical business stakeholders to understand needs and convert them into well-defined technical solutions.
- Drive architecture and design decisions for agentic systems, owning tradeoffs across scalability, reliability, and risk across multiple teams.
Profil recherché
- Track record of setting technical standards, leading design/architecture reviews, and mentoring engineers. This role carries a formal technical leadership expectation- Deep proficiency in context engineering including prompt design, retrieval strategies, and memory/context management
- Hands-on experience building tools and integrations for LLM-based systems
- Experience with LLM evaluation, observability, and benchmarking as core engineering practice
- 3+ years of professional experience in applied AI (building agents, MCP servers, context/harness engineering)
- Strong programming skills (language agnostic, Python strongly preferred)
- Proven experience building and deploying AI solutions in production environments, including familiarity with agent frameworks and a clear understanding of what they do and why they matter
- Either: A Bachelor's or Master's degree in Computer Science, Engineering, or related field OR Equivalent demonstrated experience
- Strong written and verbal communication skills, particularly the ability to explain complex AI concepts to non-technical audiences
- Demonstrated ability to work directly with non-technical stakeholders to scope AI opportunities and define technical requirements
- 7-10+ years of relevant professional experience in software engineering, with increasing seniority
- Ability to work independently, manage ambiguity, and deliver results without close oversight
- 10-15+ years of overall professional experience, including 5+ years in applied AI
- Prior experience owning an AI scoping or discovery practice, not just executing against pre-defined specs
- Experience in a consulting, platform, or internal services capacity and experience managing multiple workstreams
- Familiarity with AWS and/or Snowflake in a production context
- Experience with NLP tasks such as summarization, classification, or entity extraction and their application in agentic contexts
- Contributions to AI strategy, roadmap definition, or architectural decision-making at an organizational level