It is an exciting time to join Fisher Investments! We are expanding our Generative AI capabilities to support our international growth. We are looking for a Software Engineer who will design, build, and improve advanced AI applications using large language models, GPU‑accelerated computing, and modern API frameworks.
The Opportunity:
The Software Engineer will architect, implement, and improve production-ready generative AI systems, working closely with AI leads, ML engineers, and platform teams. You will develop solutions powered by LLMs, context engineering, and GPU-accelerated frameworks, using Azure, Databricks, graph databases, and scalable microservices to deliver high-performance, secure applications integrated with enterprise systems. You will report to the AI Team Leader, Technology Innovation.
The Day-to-Day:
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
Your Qualifications:
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)
Why Fisher Investments:
We work for a bigger purpose: bettering the investment universe. We take great pride in our inclusive culture, our learning and development framework customized for every employee, and our Great Place to Work Certification. It's the people that make the Fisher purpose possible, and we invest in them by offering exceptional benefits like:
100% paid medical, dental and vision premiums for you and your qualifying dependents
A 50% 401(k) match, up to the IRS maximum
20 days of PTO, plus 10 paid holidays
Family Support programs including 8 week Paid Primary Caregiver Leave, $10,000 fertility, family forming, and hormonal health assistance, and back-up child, adult, and elder care
This is an…