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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer / AI Engineer, AVP - **Company:** Mitsubishi UFJ Financial Group - **Location:** Jersey City, NJ, United States (Remote available) - **Experience:** Expert - **Salary:** $100,000 - $171,000 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Automation of Tests, Software as a Service, Cloud Computing, Cloud Engineering, Cyber Security, Computer Programming, Databases, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Security, Data Systems, Relational Databases, Database Development, DevOps, IBM WebSphere MQ, Python (Programming Language), PostgreSQL, Machine Learning, Meta-Data Management, Language Modeling, Operational Data Store, OpenShift, Systems Development Life Cycle, Query Optimization, Cloud Services, DataOps, Search Technologies, Software Engineering, SQL Databases, Systems Integration, Unstructured Data, Workflow Management Systems, Enterprise Search, Data Logging, Enterprise Software Applications, Data Ingestion, Spring Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Hallucination Detection, Model Validation, Software Application Programming, Generative AI, Indexer, Agentic-AI, Event Driven Architecture, Containerization, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Enterprise Integration, AWS Data Analytics, Apache Kafka, Data Management, Machine Learning Operations, Invoking Functions, Api Design, Data Pipelines, Automation Anywhere, Docker, Legacy Systems, Programming Languages - **Published:** November 11, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-ai-engineer-avp-jersey-city-nj--dd713d64-b10d-464d-97d6-395187ec1838 ## About the Role Artificial Intelligence (AI), Team Lead/Manager, Cloud Computing, Software Engineering, Artificial Intelligence (AI), Scalable System Development, Artificial Intelligence (AI) Programming Languages, Modeling Languages, Financial Transactions, Automation, * 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 ## Description 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., * 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.