Required Skills & Experience
- 4+ years of dedicated AI/ML Engineering experience
- Proven experience owning and delivering AI initiatives from business requirements through architecture, development, deployment, and ongoing optimization, including the design and implementation of AI agents
- Hands-on experience designing, building, and deploying end-to-end LLM-powered applications and AI agents utilizing platforms such as Anthropic Claude, Microsoft Copilot, AWS Bedrock, OpenAI GPT, Google Gemini, Llama, and Mistral. ○ Experience should include model selection, prompt engineering, Retrieval-Augmented Generation (RAG), grounding strategies, hallucination mitigation, model evaluation, optimization, and production deployment. ○ Experience designing agentic workflows and multi-step AI orchestration frameworks ○ Experience integrating LLM applications with enterprise systems, APIs, databases, document repositories, and business processes
- Experience building agentic AI solutions utilizing orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, LlamaIndex, or similar technologies
- Experience building and scaling AI/LLM solutions within enterprise cloud environments, preferably Microsoft Azure (Azure OpenAI, Azure ML, Databricks, ADLS, Azure AI Search). Comparable AWS experience (Bedrock, SageMaker, AI/ML Services) or other cloud AI platforms will also be considered.
- Experience deploying AI applications into production environments with monitoring, governance, and continuous improvement processes
- Strong Python development experience
- Banking and/or Financial Services industry experience with experience supporting banking functions such as lending, loan operations, payments, fraud monitoring, risk, customer service, or operational efficiency initiatives.
- Strong communication and presentation skills
Nice to Have Skills & Experience
- Experience developing enterprise copilots, digital assistants, knowledge-management solutions, or employee productivity platforms
- Experience supporting customer analytics, risk analytics, fraud analytics, or operational intelligence initiatives
- Demonstrated ability to provide technical leadership, mentor team members, and drive engineering best practices across complex AI initiatives.
- Experience operating within regulated environments, with an understanding of AI governance, model risk management, vendor partnerships, data privacy requirements, and compliance-focused technology delivery.
Job Description
A Financial Services client is seeking an AI Engineer to join their team! This individual will partner with stakeholders across lending, loan operations, payments, marketing, HR, fraud, and other business units to design, develop, and deploy AI solutions that increase productivity and automate manual processes. The AI Engineer will build and support AI agents, LLM-powered applications, copilots, RAG solutions, and workflow automation tools utilizing technologies such as Claude, Microsoft Copilot, AWS Bedrock, Python, and modern orchestration frameworks. Responsibilities include evaluating and prioritizing business use cases, integrating AI solutions with enterprise systems and data sources, optimizing model performance, and driving projects from concept through production deployment. This individual will serve as a hands-on technical contributor responsible for owning AI initiatives end-to-end while helping scale the organization's enterprise AI capabilities and long-term strategy. The ideal candidate will be comfortable engaging directly with business stakeholders, identifying opportunities for automation, and translating business challenges into scalable AI solutions. This is a full-time permanent opportunity offering a base salary of $130,000-$225,000 plus bonus and potential equity. The position can sit in Pasadena, CA, Palo Alto, CA, Dallas, TX, or New York, NY and requires a hybrid schedule with 4 days onsite per week.