chicago, il, United States Full Time Posted 1 day ago
Education & Experience
Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, or a related field, or equivalent work experience
Minimum 3-7 years of relevant work experience
Experience working within an Agile/SCRUM environment
Experience delivering and supporting machine learning and AI solutions in production environments
Experience with the machine learning lifecycle, including development, deployment, monitoring, governance, and retirement
Experience with Generative AI, Large Language Models (LLMs), and foundation models
Experience building AI-powered applications and services
Experience designing and implementing AI agents and agentic workflows with responsible AI and human oversight controls
Experience with machine learning libraries and frameworks
Experience with AI orchestration frameworks
Experience with vector databases, embeddings, and semantic search technologies
Experience with ML Ops, AI Ops, and model lifecycle management frameworks
Experience working with databases, data lakes, and modern data platforms
Experience building cloud-native applications, services, CI/CD pipelines, and Infrastructure as Code (IaC)
Experience with cloud computing platforms, specifically Amazon Web Services technologies such as SageMaker, Bedrock, Docker, Lambda, and Kubernetes
Experience troubleshooting production applications, AI systems, and cloud infrastructure
Experience integrating AI solutions with enterprise systems, APIs, and third-party platforms
Strong Python programming experience
Knowledge & Abilities
An ability to adopt new ways of working and embrace new technologies and techniques
Dynamic communication skills with a focus on building relationships by listening and asking questions
Extensive and effective presentation skills
Strong leadership and team building skills
Ability to establish and communicate priorities, constraints, deadlines, and goals
Ability to develop strong trust relationships with stakeholders
Strong organizational skills and experience with formal SDLC
Ability to solve complex problems and think analytically
Highly self-motivated and directed
Ability to absorb and retain information quickly
Ability to present technical concepts in user-friendly language
Possess an agile mindset and openness to adaptation based on experience and feedback
Strong attention to detail and a focus on long-term strategic quality
Promote a culture of collaboration, innovation, and continuous improvement
Consistently participate in diversity, equity and inclusion (DEI) events and use a DEI perspective to enhance the Bank’s culture and positively impact our business, members, and communities
Strong understanding of machine learning, deep learning, Generative AI, LLMs, embeddings, vector search, prompt engineering, and RAG
Understanding of AI agent architecture, tool use, multi-agent patterns, and workflow orchestration
Understanding of Responsible AI principles, model governance, AI risk management, security, privacy, and regulatory considerations
Ability to design AI solutions that balance innovation and business value with security, compliance, human oversight, and operational reliability
Ability to evaluate AI, ML, and agent performance using quantitative and qualitative methods
Ability to troubleshoot model drift, hallucinations, unintended agent behavior, performance degradation, and operational issues