Artificial Intelligence Engineer

Artificial Intelligence Engineer

📍 Location: San Francisco, CA, US

🏢 Industry: Financial Services

💼 Work Setting: On Site

Are you passionate about building next-generation AI systems, advancing large language model capabilities, and creating scalable platforms that bring cutting-edge AI solutions into production? We are seeking an AI Engineer

to design, develop, and deploy enterprise-grade AI systems that support foundation models, large language models (LLMs), agentic AI workflows, and responsible AI initiatives.

In this role, you will work at the intersection of machine learning, distributed systems, and software engineering to deliver robust AI solutions that scale across enterprise environments. You will collaborate with research, engineering, product, and infrastructure teams to translate innovative AI concepts into production-ready applications and platforms.

AI System

Design & Development

• Design, develop, and deploy scalable AI software components that support enterprise AI initiatives.
• Build intelligent systems leveraging foundation models, large language models, and advanced machine learning techniques.
• Develop reusable AI frameworks, services, and tools that accelerate innovation and deployment.
• Ensure solutions are scalable, reliable, and maintainable across production environments.

Large Language Models & Generative AI

• Build and optimize applications powered by large language models (LLMs).
• Support model inference, prompt orchestration, context management, and performance optimization.
• Integrate foundation models into enterprise workflows and business applications.
• Evaluate emerging AI technologies and identify opportunities for innovation.

Agentic AI & Automation

• Design and implement agentic AI workflows capable of autonomous task execution and decision support.
• Develop intelligent agents that interact with enterprise systems, APIs, and business processes.
• Create orchestration frameworks that enable complex multi-step AI workflows.
• Improve automation capabilities through AI-driven solutions.

AI Infrastructure & Platform Engineering

• Build infrastructure that supports training, deployment, monitoring, and operation of AI applications.
• Design scalable architectures that support AI workloads across cloud and distributed environments.
• Optimize system performance, availability, and resource utilization.
• Support platform reliability and operational excellence initiatives.

Model Governance & Responsible AI

• Develop frameworks and controls that support responsible AI implementation.
• Ensure compliance with governance, security, privacy, and risk management requirements.
• Support model monitoring, validation, auditing, and lifecycle management processes.
• Promote ethical and transparent AI practices across development efforts.

Performance Optimization & Scalability

• Analyze and optimize AI systems for latency, throughput, scalability, and cost efficiency.
• Improve inference performance and system responsiveness.
• Implement monitoring and observability practices for AI services.
• Perform troubleshooting and root cause analysis for complex AI platform issues.

Research-to-Production Enablement

• Collaborate with AI researchers and data scientists to operationalize innovative models and algorithms.
• Translate experimental AI technologies into production-ready solutions.
• Support testing, validation, benchmarking, and deployment activities.
• Help establish best practices that bridge research and production engineering.

Technical Leadership & Collaboration

• Partner with product, engineering, data science, and infrastructure teams to deliver AI-driven solutions.
• Contribute to architectural decisions, technical standards, and development methodologies.
• Mentor engineers and provide guidance on scalable AI system design.
• Foster a culture of innovation, learning, and engineering excellence.

Required Qualifications

• Bachelor's or Master's degree in:
• Computer Science
• Software Engineering
• Artificial Intelligence
• Machine Learning
• Data Science
• Related technical field
• 2–4+ years of experience in AI/ML engineering, software engineering, or related technical roles.
• Experience developing and deploying AI or machine learning applications.
• Strong programming proficiency in:
• Python
• Go
• Java
• Similar modern programming languages
• Strong understanding of machine learning fundamentals and software engineering principles.
• Experience working in collaborative, cross-functional engineering environments.

Key Technical Skills

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Large Language Models (LLMs)
• Foundation Models
• Agentic AI
• AI Infrastructure
• Distributed Systems
• Python
• Go
• Java
• Model Optimization
• AI Governance
• Generative AI
• API Development
• Cloud Computing
• Software Architecture
• Model Deployment
• Scalable Systems Design
• Performance Engineering
• Responsible AI

Preferred Qualifications

• Experience deploying AI applications into production environments.
• Knowledge of modern AI orchestration frameworks and agent architectures.
• Experience with cloud-based AI platforms and infrastructure services.
• Familiarity with distributed computing and large-scale system design.
• Understanding of AI monitoring, governance, and operational best practices.
• Experience mentoring engineers and contributing to technical leadership initiatives.