Artificial Intelligence AI LLM Engineer

Job Description

***Position is bonus eligible***

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Prestigious Financial Institution is currently seeking an Artificial Intelligence Engineer with strong LLM experience Candidate will be responsible for the design and delivery of agentic AI systems end-to-end, from architecture through production deployment.

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Responsibilities:

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• Architect agent orchestration patterns, tool and context integration, and evaluation pipelines for reliability in a regulated environment

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• AI infrastructure supporting agents and applications on AWS, and contribute to the team's growing infrastructure self-sufficiency

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• Implement technical safeguards against AI-specific risks, including hallucination detection, prompt injection defense, and output validation, in collaboration with AI Governance function

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• Build audit logging and human-in-the-loop checkpoints into agentic workflows so agent actions remain traceable and reviewable in a regulated environment

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• Mentor Associate and Senior Associate engineers through code and architecture review

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• Contribute technical point of view to the team's evolving engineering standards and practices, in partnership with the Executive Director

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Qualifications:

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• Experience mentoring or elevating the work of junior engineers

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• Demonstrated ownership of production systems from design through deployment

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• Ability to work effectively in a still-forming, fast-moving team environment

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• This position is not eligible for employment be legally authorized to work in the United States without the need for sponsorship now or in the future.

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• Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's preferred

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• 4-7 years of software engineering experience, with production AI/LLM systems experience preferred

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Technical Skills:

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• Required: Strong Python; proficient SQL; solid distributed systems and API design fundamentals

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• Required: Hands-on experience building LLM-powered applications or agentic systems

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• Required: Working knowledge of AI-specific risk areas (prompt injection, output validation, hallucination mitigation, data privacy), or demonstrated ability to build this expertise quickly

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• Required: Cloud infrastructure experience (AWS preferred); comfort with Docker, CI/CD, and containerization fundamentals

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• Preferred: Direct experience with Claude, the Anthropic API, or Claude.ai/Console

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• Preferred: Experience designing agent orchestration or Model Context Protocol (MCP)-based integrations

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• Preferred: Production experience operating LLM-powered applications or agentic systems at scale

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• Preferred: Kubernetes and infrastructure-as-code (Terraform)

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• Preferred: Background in financial services, derivatives, or other regulated industries

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• Preferred: Exposure to AI security practices such as red-teaming or adversarial testing of model inputs and outputs

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• Preferred: Data engineering experience (pipelines, data modeling), particularly for candidates interested in AI infrastructure work

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