Why This Role Stands Out
This role offers a unique opportunity to architect and operationalize cutting-edge generative AI solutions, providing significant career growth as you evolve into a platform owner for enterprise AI standards. You'll thrive here if you possess deep experience in AI engineering and are eager to build impactful, enterprise-grade AI systems. Apply today to shape the future of AI within a dynamic lending environment.
Quick Overview
Job Description
Applied AI Engineer
New York City, NY (Hybrid - 3 days onsite, LOCALS ONLY)
12 MONTHS CONTRACT
Our client is seeking an Applied AI Engineer with 10+ years of experience to design, build, and operationalize generative AI solutions across their Lending business lines.
This role offers the opportunity to architect enterprise-grade GenAI workflows, establish LLMOps best practices, and evolve into a platform owner for shared AI standards.
Responsibilities & Qualifications
•Design and evolve reusable GenAI workflows and agentic systems deployed across multiple Lending business units
•Develop enterprise-grade AI-powered document ingestion, data extraction, and content generation capabilities
•Build AI assistants embedded in Lending systems using agentic workflows and orchestration patterns
•Deliver automated workflows for content generation, reporting, and approval processes
•Establish and operationalize LLMOps practices including extraction accuracy monitoring, prompt management, and audit controls
•Design and implement security controls for entitlements, PII handling, and governance within AI systems
•Provide expert technical guidance on GenAI architecture, model selection, and platform orchestration decisions
•Act as hands-on technical expert with a clear advancement path to platform owner for enterprise GenAI standards
Requirements
•10+ years of software engineering experience with demonstrated expertise in generative AI solutions
•Strong proficiency with Lang Chain, LLM platforms, and RAG (Retrieval-Augmented Generation) architectures
•Production-level experience with Python or Java and building scalable ML systems
•Hands-on expertise in agentic workflows, vector search, prompt management, and data ingestion pipelines
•Deep understanding of LLMOps practices including model monitoring, logging, and production reliability
•Experience designing and implementing data pipelines and working with large language models in enterprise environments
•Strong grasp of AI security, compliance, and governance requirements for financial services or similarly regulated industries
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