OverviewWe 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)
Compensation:- $130,000 - $185,000 base salary per year in the state of WA. New hires should expect to start at the lower end of the range depending on experience
- Eligible for a discretionary bonus based on firm and individual performance
- 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 in-office role. Based on your role, tenure, and performance eligibility you may have the opportunity to participate in our hybrid work from home program. This program is subject to change.
