Artificial Intelligence Engineer / Data

• Data engineering (currently highest preference): ETL/ELT, data pipelines - Needs to build a “knowledge substrate” to make corporate data (ServiceNow, JIRA, SaaS apps) consumable by AI models
• Software/application engineering: building agentic workflows
• Infrastructure: AWS infrastructure-as-code, containerization, deployment pipelines

Technical Skills:

• Required: Strong Python; proficient SQL; solid distributed systems and API design fundamentals
• Required: Hands-on experience building LLM-powered applications or agentic systems
• Required: Working knowledge of AI-specific risk areas (prompt injection, output validation, hallucination mitigation, data privacy), or demonstrated ability to build this expertise quickly
• Required: Cloud infrastructure experience (AWS preferred); comfort with Docker, CI/CD, and containerization fundamentals
• Preferred: Direct experience with Claude, the Anthropic API, or Claude.ai/Console
• Preferred: Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations
• Preferred: Production experience operating LLM-powered applications or agentic systems at scale
• Preferred: Kubernetes and infrastructure-as-code (Terraform)
• Preferred: Background in financial services, derivatives, or other regulated industries
• Preferred: Exposure to AI security practices such as red-teaming or adversarial testing of model inputs and outputs
• Preferred: Data engineering experience (pipelines, data modeling), particularly for candidates interested in AI infrastructure work, * Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master’s preferred
• 4-7 years of software engineering experience, with production AI/LLM systems experience preferred