AI Foundational Model Engineer
$149k - $205kMUFG Bank, Ltd.
Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.
With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.
Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.
The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.
Vice President – Technical AI Foundation Model Engineer Role SummaryThe VP, Technical AI Foundation Model Engineer is responsible for designing, building, deploying, and optimizing enterprise-grade AI solutions powered by foundation models, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI architectures. The role translates AI concepts into secure, scalable, observable, and production-ready systems suitable for a highly regulated financial services environment.
This individual serves as the technical lead across AI engineering initiatives, partnering closely with Product Management, Enterprise Architecture, Data Engineering, Platform Engineering, Cybersecurity, Risk, and Business stakeholders to deliver transformational AI capabilities.
Key Responsibilities Foundation Model Engineering- Design, build, and optimize enterprise AI solutions leveraging foundation models, LLMs, and agentic AI architectures.
- Develop and maintain Retrieval-Augmented Generation (RAG) pipelines and semantic search capabilities.
- Evaluate, benchmark, and recommend foundation models based on performance, cost, security, explainability, and business requirements.
- Implement model orchestration, prompt engineering, agent frameworks, and AI workflow automation. [[MUFG AI Ge...ck Revised | PDF]]( us mufg jp/Documents/Microsoft%20Teams%20Chat%20Files/MUFG AI GenAI Search JD Pack Revised.pdf?web=1)
- Lead solution architecture for AI applications across cloud and enterprise platforms.
- Design scalable model-serving architectures and AI APIs.
- Optimize latency, throughput, resiliency, and cost efficiency of AI workloads.
- Establish reusable frameworks and engineering patterns for enterprise AI delivery.
- Own end-to-end model lifecycle management, including:
- Experimentation
- Evaluation
- Deployment
- Monitoring
- Rollback
- Continuous improvement
- Implement observability, telemetry, and performance monitoring across AI solutions.
- Define engineering standards and best practices for AI development and operations
- Ensure AI systems comply with enterprise requirements for:
- Security
- Privacy
- Risk Management
- Compliance
- Auditability
- Implement controls for:
- Hallucination mitigation
- Prompt security
- Model safety
- Data protection
- Human oversight
- Partner with Model Risk Management, Legal, and Compliance teams to operationalize Responsible AI principles.
- Lead technical design reviews and architecture decisions.
- Mentor engineers and establish engineering excellence practices.
- Guide build-vs-buy evaluations for AI platforms and vendor solutions.
- Drive innovation through experimentation with emerging AI technologies.
- Translate business requirements into scalable AI architectures.
- Collaborate with Product Managers and business teams to define solution requirements.
- Present technical recommendations and tradeoffs to senior leadership.
- Support executive decision-making regarding AI platform investments.
- 8-12+ years of experience in:
- AI/ML Engineering
- Software Engineering
- Platform Engineering
- Applied Machine Learning
- Demonstrated experience delivering production-grade AI solutions.
- Previous experience building enterprise-scale AI platforms or AI-enabled products.
- Experience working in regulated industries such as banking, financial services, insurance, healthcare, or government preferred
Strong hands-on expertise in:
AI & Machine Learning- Foundation Models
- Large Language Models (LLMs)
- Agentic AI Systems
- Retrieval-Augmented Generation (RAG)
- Embeddings
- Semantic Search
- Vector Databases
- Prompt Engineering
- Fine-Tuning Techniques
- Python
- PyTorch
- TensorFlow
- Hugging Face
- LangChain
- LlamaIndex
- Semantic Kernel
- AWS and/or Azure
- Kubernetes
- Containerized AI Workloads
- CI/CD Pipelines
- Model Serving Platforms
- API Architecture
- MLOps
- LLMOps
- Model Monitoring
- Evaluation Frameworks
- Performance Optimization
- Cost Optimization
- Strong architecture and systems-thinking mindset.
- Ability to influence across engineering, product, architecture, and risk organizations.
- Executive communication skills.
- Strong problem-solving and decision-making capability.
- Ability to balance innovation with governance requirements.
- Experience leading technical teams and mentoring engineers.
The VP, Technical AI Foundation Model Engineer will be measured on:
Platform & Engineering Outcomes- Production AI deployments
- Platform reliability and scalability
- Performance optimization
- Engineering productivity
- Model accuracy
- Retrieval effectiveness
- Hallucination reduction
- User adoption and satisfaction
- AI platform utilization
- Cost efficiency
- Time-to-production
- Technical debt reduction
- Compliance adherence
- Security posture
- Responsible AI control effectiveness
- Audit readiness
- Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience
- New York / New Jersey: $149-205K
- Non–New York / New Jersey: $149-188K
We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws (including (i) the San Francisco Fair Chance Ordinance, (ii) the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, (iii) the Los Angeles County Fair Chance Ordinance, and (iv) the California Fair Chance Act) to the extent that (a) an applicant is not subject to a statutory disqualification pursuant to Section 3(a)(39) of the Securities and Exchange Act of 1934 or Section 8a(2) or 8a(3) of the Commodity Exchange Act, and (b) they do not conflict with the background screening requirements of the Financial Industry Regulatory Authority (FINRA) and the National Futures Association (NFA). The major responsibilities listed above are the material job duties of this role for which the Company reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of conditional offer of employment, if any.
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.
We are proud to be an Equal Opportunity Employer and committed to leveraging the diverse backgrounds, perspectives and experience of our workforce to create opportunities for our colleagues and our business. We do not discriminate on the basis of race, color, national origin, religion, gender expression, gender identity, sex, age, ancestry, marital status, protected veteran and military status, disability, medical condition, sexual orientation, genetic information, or any other status of an individual or that individual’s associates or relatives that is protected under applicable federal, state, or local law.
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