AI Engineer – Data and AI
About The Position
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 an AI Engineer who will design, build, and optimize advanced AI applications leveraging large language models, GPU‑accelerated computing, and modern API frameworks. The Opportunity: The Day-to-Day: Design, develop, fine-tune, and deploy generative AI models into scalable production environment 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 Ensure AI models are explainable, reliable, and compliant with regulatory and internal governance standards Continuously monitor and optimize model performance using evaluation frameworks, observability tools, and iterative fine-tuning
Requirements
- 8+ years of IT industry experience
- Minimum 2+ years of hands-on AI development experience
- 3+ years of experience in Python programming
- Proficient in Python with practical experience in LLMs, embeddings, vector databases and RAG architecture.
- Demonstrated experience with generative AI models, including multimodal models
- Hands-on experience with Hands-on experience with cloud-native AI infrastructure, including Azure AI Foundry or AWS Bedrock, Open AI Models and AI model governance frameworks
- Bachelor's degree in Computer Science, AI, or a related field (or equivalent professional experience)
Nice To Haves
- GPU-accelerated training and inference using NVIDIA technologies, including NIM and NeMo frameworks
- Optimize and scale AI models with NVIDIA NIM, and fine-tuning models with NeMo services
- Familiarity with AI agentic frameworks and deploying AI agents in production environments
- Deploy models with low latency and high throughput, using frameworks like vLLM and other GPU model deployment tools
- CI/CD pipelines for ML and Generative AI workflows, along with containerization and orchestration (Docker, Kubernetes)
Responsibilities
- Design, develop, fine-tune, and deploy generative AI models into scalable production environment
- 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
- Ensure AI models are explainable, reliable, and compliant with regulatory and internal governance standards
- Continuously monitor and optimize model performance using evaluation frameworks, observability tools, and iterative fine-tuning
Benefits
- 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
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
