Role Overview:

The MLOps Engineer - Analyst (Gen AI Focus) will support the deployment, monitoring, and optimization of Generative AI solutions across the enterprise AI ecosystem, including LLM-based applications, copilots, and AI agents

This entry-level role is designed for recent graduates looking to work at the intersection of Generative AI, cloud platforms, and enterprise-scale operations, with a focus on responsible AI, governance, and production readiness in a regulated banking environment.

Key Responsibilities:

1) Gen AI Application Deployment & Support

• Assist in deploying and managing LLM-powered applications (chatbots, copilots, AI agents).
• Support integration of Gen AI models (e.g., prompt workflows, APIs, retrieval layers) into enterprise systems.
• Help onboard business use cases onto enterprise platforms.

2) Prompt Engineering & Optimization Support

• Support creation, testing, and refinement of prompts and prompt templates.
• Assist in evaluating response quality, consistency, and hallucination risks.
• Work with senior engineers to improve accuracy, grounding, and reliability of AI outputs.

3) Retrieval-Augmented Generation (RAG) & Data Integration

• Assist in building and testing RAG pipelines (connecting Gen AI models with enterprise data).
• Support data ingestion, indexing, and validation workflows.
• Help ensure responses are grounded in approved enterprise data sources.

4) Monitoring & Evaluation of Gen AI Systems

• Monitor Gen AI systems for: Output quality, Latency and performance, Safety and compliance issues.
• Support creation of evaluation metrics and test datasets for Gen AI use cases.
• Assist in identifying and escalating issues such as hallucination, bias, or drift.

5) Automation & MLOps Enablement

• Contribute to automation of LLM lifecycle workflows (deployment, testing, monitoring).
• Assist in building reusable workflows using: CI/CD pipelines, API integrations, Low-code/no-code automation tools.

6) AI Governance, Risk & Responsible AI

• Follow enterprise AI governance standards for: Model usage, Prompt logging and monitoring, Data privacy and compliance.
• Assist in documenting Gen AI use cases for audit and regulatory purposes.
• Support enforcement of Responsible AI principles (fairness, explainability, security).

7) Collaboration & Learning

• Partner with: AI engineers, Data scientists, Business teams
• Participate in use case onboarding, PoCs, and production scaling efforts.
• Continuously build knowledge in Gen AI tools, frameworks, and best
• practices.

Qualifications:

Required (Entry-Level)

• Bachelor's degree in: • Advanced degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, or related field, or equivalent work experience equally preferable.
• Foundational knowledge of: Python, APIs and REST services, Machine Learning basics, and Basic understanding of Large Language Models (LLMs).

Preferred:

• Exposure to: Generative AI (e.g., ChatGPT, Azure OpenAI, LLM APIs); Prompt engineering concepts; Vector databases / embeddings (basic familiarity); Cloud platforms (AWS, Azure).
• Academic projects or internships involving AI/ML or Gen AI.

Key Skills:

Technical Skills:

• Python / scripting.
• LLM fundamentals (prompting, inference, evaluation).
• API integration and data handling.
• Basic cloud & DevOps concepts.

Behavioral Skills:

• Analytical thinking and curiosity (critical for Gen AI experimentation).
• Attention to detail (important for model validation and risk control).
• Strong communication and collaboration skills.
• Willingness to learn quickly in a fast-evolving AI landscape.

Education:
• Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience

"Visa sponsorship/support is based on business needs. We do not anticipate providing visa sponsorship/support for this position."

The typical base pay range for this role is as follows:

• New York / New Jersey: $107-$133K
• Non- New York/New Jersey- $103-129K

depending on job-related knowledge, skills, experience and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation. Additionally, our Total Rewards program provides colleagues with a competitive benefits package (in accordance with the eligibility requirements and respective terms of each) that includes comprehensive health and wellness benefits, retirement plans, educational assistance and training programs, income replacement for qualified employees with disabilities, paid maternity and parental bonding leave, and paid vacation, sick days, and holidays. For more information on our Total Rewards package, please click the link below.

Our hybrid work schedule is four days on-site and work remotely one day per week.

MUFG Benefits Summary

The above statements are intended to describe the general nature and level of work being performed. They are not intended to be construed as an exhaustive list of all responsibilities duties and skills required of personnel so classified.