AI Engineer

Fisher Investments is hiring an AI Engineer in Tampa, FL to design, develop, and deploy production-ready generative AI systems. The role focuses on building LLM-powered solutions with GPU-accelerated computing, integrating secure cloud architectures, and delivering reliable performance through evaluation and monitoring.

Responsibilities

• Design, develop, fine-tune, and deploy generative AI models into scalable production environments
• Build and maintain APIs and microservices using FastAPI to expose AI capabilities enterprise wide
• Collaborate with the AI Infrastructure team to architect robust LLM pipelines, including training workflows and retrieval-augmented generation (RAG) systems
• Integrate AI solutions into enterprise applications using secure, cloud-native architectures and best practices
• Build and operate data ingestion, transformation, and orchestration pipelines using Databricks, Delta Lake, Auto Loader, and Workflows to support AI applications and retrieval systems
• Integrate graph databases into AI applications to model relationships and support graph-enhanced RAG and hybrid retrieval solutions
• Ensure AI models are explainable, reliable, and compliant with regulatory and internal governance standards
• Monitor and improve application and model performance using evaluation frameworks, observability tools, and iterative improvements to prompts, retrieval, context, and model configuration

Requirements

• Minimum of 6+ years of experience building data-driven software solutions
• Minimum of 3+ years of hands-on AI development experience
• Proficiency in Python, with practical experience building applications using LLMs, embeddings, vector databases, and RAG architecture
• Demonstrated experience with generative AI models, including multimodal models
• Hands-on experience developing and deploying AI applications using Azure Foundry, Docker, Kubernetes, and GPU-backed compute
• Bachelor’s degree in computer science, Artificial Intelligence, or a related field, or equivalent professional experience
• Experience fine-tuning, evaluating, and deploying models using Azure-managed AI services and compute resources
• Familiarity with agent frameworks and experience deploying AI agents with tool integration, appropriate permissions, and operational safeguards
• Experience building graph-enhanced RAG and hybrid retrieval solutions using graph databases such as Neo4j, Stardog, or Azure Cosmos DB for Apache Gremlin
• Experience deploying models with low latency and high throughput, using frameworks like vLLM and other GPU model deployment tools
• Hands-on experience building CI/CD pipelines and automated testing workflows for generative AI application
• Experience with distributed training, GPU optimization, and large-scale model frameworks (CUDA, RAPIDS)

Technologies

• Large language models (LLMs), GPU-accelerated computing
• FastAPI, Azure, Databricks
• Graph databases: Neo4j, Stardog, Azure Cosmos DB for Apache Gremlin
• Azure Foundry, Docker, Kubernetes
• Databricks Delta Lake, Auto Loader, Workflows
• Embeddings, vector databases, retrieval-augmented generation (RAG)
• Multimodal models, RAG architecture, agent frameworks
• CI/CD pipelines, observability tools
• vLLM, CUDA, RAPIDS

Benefits

• 100% paid medical, dental and vision premiums for you and your qualifying dependents
• 50% 401(k) match, up to the IRS maximum
• 20 days of PTO, plus 10 paid holidays
• 8 week Paid Primary Caregiver Leave
• $10,000 fertility, family forming, and hormonal health assistance
• Back-up child, adult, and elder care
• In-office role with potential opportunity to participate in a hybrid work from home program (subject to change)

Role Details

Location: Tampa, FL (onsite)

Experience: 6+ years

Education: Bachelor’s degree in computer science, Artificial Intelligence, or a related field, or equivalent professional experience