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Senior AI Engineer (Agentic AI) – Associate Principal
New York Technology Partners
1 hour ago
Full-time
On-site
Chicago, Illinois, United States
AI Research & Engineering (AIRE) team is launching a high-visibility, greenfield initiative to build the company’s first generation of agentic AI capabilities. We are seeking a highly collaborative and technically versatile AI Engineer to own the design and delivery of these systems end-to-end.
In this role, you will focus on making internal corporate data (e.g., ServiceNow, JIRA) highly consumable and actionable for advanced AI models, such as Anthropic’s Claude, running on AWS infrastructure. This is a foundational opportunity to shape our AI application and infrastructure standards while mentoring a team of junior engineers.
Note: This role focuses exclusively on internal corporate data, not clearing data. Key Responsibilities End-to-End Delivery:
Own the architecture, design, and production deployment of agentic AI systems and supporting data infrastructure. Data & AI Integration:
Build and optimize data pipelines and data warehousing solutions to ensure high-quality, model-ready corporate data. AI Governance & Security:
Implement technical safeguards against AI-specific risks, including hallucination detection, prompt injection defense, and output validation, in collaboration with OCC’s AI Governance function. Mentorship:
Guide and elevate the work of junior engineers (including recent graduates) through hands-on mentorship, code reviews, and architecture discussions. Cross-Functional Collaboration:
Partner with stakeholders across the organization to define engineering standards, evaluate new AI tools, and ensure traceable, human-in-the-loop workflows in a regulated environment. Qualifications & Experience Experience:
4–7 years of professional experience in Data Engineering, Data Science, Data Analytics, or Software Engineering. Core Technical Skills:
Strong proficiency in Python and SQL, with solid fundamentals in distributed systems and API design. AI/LLM Experience:
Hands-on experience building, deploying, or integrating LLM-powered applications or agentic systems. Data Engineering:
Demonstrated experience with data pipelines, data modeling, and data warehousing. Cloud & DevOps:
Working knowledge of cloud infrastructure (AWS preferred), Docker, CI/CD, and containerization fundamentals. Risk Awareness:
Familiarity with AI-specific risk areas (e.g., prompt injection, output validation, hallucination mitigation, data privacy). Soft Skills:
Exceptional communication and collaboration skills, with a proven ability to thrive in a fast-moving, formative team environment. Preferred Qualifications Direct experience with Claude, the Anthropic API, or Claude.ai/Console. Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations. Familiarity with Kubernetes and infrastructure-as-code (e.g., Terraform). Prior exposure to AI security practices, such as red-teaming or adversarial testing. Background in financial services, derivatives, or other regulated industries
(Note: Financial experience is a plus, but not required) . Education Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field (Master’s degree preferred).
Note: This role focuses exclusively on internal corporate data, not clearing data. Key Responsibilities End-to-End Delivery:
Own the architecture, design, and production deployment of agentic AI systems and supporting data infrastructure. Data & AI Integration:
Build and optimize data pipelines and data warehousing solutions to ensure high-quality, model-ready corporate data. AI Governance & Security:
Implement technical safeguards against AI-specific risks, including hallucination detection, prompt injection defense, and output validation, in collaboration with OCC’s AI Governance function. Mentorship:
Guide and elevate the work of junior engineers (including recent graduates) through hands-on mentorship, code reviews, and architecture discussions. Cross-Functional Collaboration:
Partner with stakeholders across the organization to define engineering standards, evaluate new AI tools, and ensure traceable, human-in-the-loop workflows in a regulated environment. Qualifications & Experience Experience:
4–7 years of professional experience in Data Engineering, Data Science, Data Analytics, or Software Engineering. Core Technical Skills:
Strong proficiency in Python and SQL, with solid fundamentals in distributed systems and API design. AI/LLM Experience:
Hands-on experience building, deploying, or integrating LLM-powered applications or agentic systems. Data Engineering:
Demonstrated experience with data pipelines, data modeling, and data warehousing. Cloud & DevOps:
Working knowledge of cloud infrastructure (AWS preferred), Docker, CI/CD, and containerization fundamentals. Risk Awareness:
Familiarity with AI-specific risk areas (e.g., prompt injection, output validation, hallucination mitigation, data privacy). Soft Skills:
Exceptional communication and collaboration skills, with a proven ability to thrive in a fast-moving, formative team environment. Preferred Qualifications Direct experience with Claude, the Anthropic API, or Claude.ai/Console. Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations. Familiarity with Kubernetes and infrastructure-as-code (e.g., Terraform). Prior exposure to AI security practices, such as red-teaming or adversarial testing. Background in financial services, derivatives, or other regulated industries
(Note: Financial experience is a plus, but not required) . Education Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field (Master’s degree preferred).