AI/ML Engineer

Job Description

Education & Experience

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• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, or a related field, or equivalent work experience
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• Minimum 3-7 years of relevant work experience
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• Experience working within an Agile/SCRUM environment
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• Experience delivering and supporting machine learning and AI solutions in production environments
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• Experience with the machine learning lifecycle, including development, deployment, monitoring, governance, and retirement
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• Experience with Generative AI, Large Language Models (LLMs), and foundation models
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• Experience building AI-powered applications and services
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• Experience implementing Retrieval-Augmented Generation (RAG) solutions
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• Experience designing and implementing AI agents and agentic workflows with responsible AI and human oversight controls
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• Experience with machine learning libraries and frameworks
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• Experience with AI orchestration frameworks
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• Experience with vector databases, embeddings, and semantic search technologies
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• Experience with ML Ops, AI Ops, and model lifecycle management frameworks
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• Experience working with databases, data lakes, and modern data platforms
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• Experience building cloud-native applications, services, CI/CD pipelines, and Infrastructure as Code (IaC)
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• Experience with cloud computing platforms, specifically Amazon Web Services technologies such as SageMaker, Bedrock, Docker, Lambda, and Kubernetes
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• Experience troubleshooting production applications, AI systems, and cloud infrastructure
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• Experience integrating AI solutions with enterprise systems, APIs, and third-party platforms
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• Strong Python programming experience
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Knowledge & Abilities

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• An ability to adopt new ways of working and embrace new technologies and techniques
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• Dynamic communication skills with a focus on building relationships by listening and asking questions
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• Extensive and effective presentation skills
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• Strong leadership and team building skills
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• Ability to establish and communicate priorities, constraints, deadlines, and goals
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• Ability to develop strong trust relationships with stakeholders
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• Strong organizational skills and experience with formal SDLC
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• Ability to solve complex problems and think analytically
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• Highly self-motivated and directed
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• Ability to absorb and retain information quickly
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• Ability to present technical concepts in user-friendly language
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• Possess an agile mindset and openness to adaptation based on experience and feedback
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• Strong attention to detail and a focus on long-term strategic quality
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• Promote a culture of collaboration, innovation, and continuous improvement
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• 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
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• Strong understanding of machine learning, deep learning, Generative AI, LLMs, embeddings, vector search, prompt engineering, and RAG
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• Understanding of AI agent architecture, tool use, multi-agent patterns, and workflow orchestration
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• Understanding of Responsible AI principles, model governance, AI risk management, security, privacy, and regulatory considerations
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• Ability to design AI solutions that balance innovation and business value with security, compliance, human oversight, and operational reliability
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• Ability to evaluate AI, ML, and agent performance using quantitative and qualitative methods
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• Ability to troubleshoot model drift, hallucinations, unintended agent behavior, performance degradation, and operational issues
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• Linux and Windows systems administration
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