Sr Agentic AI Engineer - Core Platforms
About The Position
The Inference Engineer independently designs, optimizes, and operates scalable production inference services that support enterprise AI and machine learning solutions. The role translates business and technical requirements into reliable model-serving capabilities, builds efficient integration patterns and data pipelines, and ensures solutions meet enterprise architecture standards for performance, reliability, observability, compliance, and production readiness. As part of Enterprise Technology Services, the role helps deliver and operate technology, digital, and data capabilities, platforms, and services globally. It works with platform, infrastructure, security, evaluation, application, product, and business teams to deliver scalable AI systems, including systems integrating machine-learning models, large language models, and intelligent services. The position also mentors junior and less-experienced engineers and promotes enterprise standards and engineering best practices.
Requirements
- Bachelor’s degree in Computer Science, Machine Learning, Data Science, or comparable experience.
- Advanced knowledge of machine-learning techniques and performance optimization.
- Strong understanding of AI system architectures, including LLM ecosystems, retrieval systems, orchestration frameworks, and evaluation methodologies.
- Strong knowledge of production model serving, inference optimization, GPU fundamentals, Kubernetes, APIs, and distributed systems.
- Ability to evaluate technical alternatives and make sound service-level design decisions within established architecture.
- At least 5 years of software development experience, including hands-on experience in machine learning, AI technologies, and Agentic AI solutions.
- Experience working with large language models, especially GPT-3.5/4 or similar models.
- Experience with programming languages such as Python, R, Java, or C++.
- Experience deploying AI models and pipelines using machine-learning operations tools.
- Experience with machine-learning algorithms and applying them to real-world problems.
- Experience with continuous integration/continuous deployment pipelines and containerized deployments.
- Experience delivering end-to-end AI systems in production, including design and operational ownership.
- Experience with distributed systems design, scalable APIs, and cloud-native AI infrastructure, including monitoring and optimization.
- Advanced expertise in a technical domain and moderate expertise in a different technical domain.
- Demonstrated experience independently building and operating production inference services.
- Experience with model-serving frameworks, containerized GPU workloads, and performance or reliability optimization.
- Must be eligible to work in the United States for American Express; the company will not pursue visa sponsorship.
Nice To Haves
- Advanced degree preferred.
Responsibilities
- Mentor junior AI Engineers and cross-functional colleagues, fostering excellence and innovation.
- Integrate AI models into production systems in collaboration with cross-functional teams.
- Maintain adherence to model governance, security, and compliance standards.
- Collaborate with engineers to deliver scalable AI solutions that meet technical and business requirements.
- Translate business requirements into actionable AI-driven technical solutions, models, and algorithms.
- Create end-to-end machine-learning operations pipelines for model deployment, monitoring, and maintenance.
- Collaborate with product and business teams to align technology initiatives with business objectives.
- Design and operate scalable production AI systems that integrate ML models, LLMs, and intelligent services across multiple components.
- Ensure AI systems meet enterprise standards for reliability, safety, explainability, observability, and compliance, and mentor others on best practices.
- Design and operate scalable inference services, ensuring performance, reliability, observability, and production readiness.
- Evaluate model-serving approaches and optimize latency, throughput, accelerator utilization, and cost for assigned workloads.
- Partner with platform, infrastructure, security, evaluation, and application teams.
- Independently build and operate production inference services.
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
Senior
