Senior Data Engineer / AI Engineer, AVP

Do you want your voice heard and your actions to count?

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.

About the role

We are seeking a highly skilled and motivated Data & AI Engineer to join our Transaction Banking Technology team. The ideal candidate will have strong hands-on experience in data engineering, cloud-native data platforms, Generative AI, Large Language Models (LLMs), and agentic AI solutions, with the ability to build secure, scalable, and production-ready enterprise solutions.

This role will focus on designing and engineering data pipelines, data services, AI-enabled applications, retrieval and knowledge architectures, and intelligent automation capabilities supporting Transaction Banking initiatives. The successful candidate will work with structured and unstructured data across enterprise, cloud, SaaS, and internal platforms and help establish reusable patterns for applying AI safely within a highly regulated environment.

The engineer will work closely with architecture, data, application engineering, cybersecurity, platform engineering, DevOps, and business teams to deliver modern solutions leveraging Python, SQL, AWS, PostgreSQL, OpenShift/Kubernetes, APIs, event-driven architectures, LLMs, RAG, vector search, and AI agents. Java and Spring Boot experience is beneficial for integration with existing enterprise platforms, but the primary focus of this position is Data Engineering and AI Engineering rather than traditional Java application development.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines for ingestion, transformation, enrichment, validation, and distribution of structured and unstructured enterprise data.
• Build data engineering solutions using Python, SQL, PostgreSQL, AWS data services, APIs, event-driven architectures, and cloud-native technologies.
• Design data models and persistence architectures optimized for analytics, AI/ML workloads, operational data processing, and AI retrieval use cases.
• Build and integrate Generative AI and LLM-based applications, including enterprise search, knowledge assistants, intelligent automation, and AI-enabled Transaction Banking capabilities.
• Design and implement Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, metadata management, embeddings, retrieval strategies, vector search, reranking, and context construction.
• Develop AI agents and agentic workflows capable of reasoning across enterprise data and securely interacting with approved APIs, tools, databases, and business services.
• Implement appropriate LLM orchestration, prompt engineering, tool/function calling, structured outputs, context management, and multi-step AI workflows.
• Evaluate and integrate enterprise AI capabilities and services available through platforms such as AWS Bedrock and related AWS AI/data services, as appropriate to the solution architecture.
• Build data integration patterns supporting batch, near-real-time, event-driven, API-based, and messaging-based processing, including Kafka and IBM MQ where applicable.
• Design solutions that provide appropriate data quality, lineage, observability, traceability, security, access control, and auditability, particularly for regulated banking data and AI applications.
• Establish monitoring and evaluation capabilities for AI solutions, including retrieval quality, response quality, latency, token utilization, hallucination risk, security controls, and production observability.
• Apply appropriate AI security and governance controls, including data entitlement, sensitive-data protection, prompt-injection defenses, model access controls, responsible AI practices, and human oversight where required.
• Containerize and deploy data and AI workloads to AWS and Red Hat OpenShift/Kubernetes, supporting scalable and highly available production environments.
• Build reusable services and APIs that allow AI and data capabilities to integrate with existing enterprise applications, including Java/Spring Boot-based systems where required.
• Partner with architecture, cybersecurity, DevOps, QA, platform engineering, and application teams to establish CI/CD, DataOps, MLOps and LLMOps practices for production AI and data workloads.
• Contribute to the modernization of Transaction Banking platforms by identifying opportunities to use data, Generative AI, AI agents, automation, and cloud-native technologies to simplify processes and improve engineering and business outcomes.

Qualifications

• 5+ years of engineering experience, with significant experience in data engineering, AI/ML engineering, cloud engineering, or related disciplines.
• Strong hands-on programming experience with Python and SQL. Experience with Java/Spring Boot is useful but not the primary requirement for this role.
• Strong experience designing and developing data ingestion, ETL/ELT, transformation, enrichment, and data processing pipelines.
• Strong working knowledge of PostgreSQL or comparable relational database technologies, including schema design, SQL development, indexing, query optimization, performance, and scalability.
• Hands-on experience with AWS, preferably involving data-intensive or AI-enabled cloud-native applications.
• Hands-on experience with Generative AI and Large Language Models, including building applications that integrate enterprise data with LLM capabilities.
• Practical understanding of Retrieval-Augmented Generation (RAG) architectures, including embeddings, chunking, vector search, metadata filtering, retrieval strategies, context construction, and response generation.
• Experience with or strong knowledge of AI agents and agentic application patterns, including tool/function calling, API integration, workflow orchestration, context management, and multi-agent or multi-step workflows.
• Experience with vector databases or vector-enabled search technologies and semantic retrieval concepts.
• Understanding of modern AI engineering practices including prompt engineering, structured outputs, model evaluation, guardrails, hallucination mitigation, observability, and LLMOps/MLOps.
• Experience implementing APIs, event-driven integrations, messaging, Kafka, IBM MQ, or comparable enterprise integration technologies.
• Experience with Docker, Kubernetes, Red Hat OpenShift, or comparable container platforms and deploying production workloads in cloud or hybrid environments.
• Strong understanding of data security, access controls, data privacy, encryption, auditability, cybersecurity, and governance, particularly when working with enterprise or regulated data.
• Familiarity with data quality, metadata management, data lineage, cataloging, observability, and DataOps practices.
• Experience implementing production systems using CI/CD, automated testing, monitoring, logging, infrastructure automation, and DevOps engineering practices.
• Experience integrating AI and data solutions with existing enterprise platforms, SaaS products, APIs, databases, and legacy systems.
• Strong problem-solving and communication skills with the ability to translate business problems into data architectures, AI solutions, and production engineering designs.
• Experience within financial services, payments, cash management, transaction banking, or other regulated environments is preferred.

Education

*Bachelor's degree in Computer Science or a closely-related discipline or relevant work experience

The typical base pay range for this role is as follows

• New York / New Jersey: $100k - $171k 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.