> Markdown version of [/jobs/ext/4629104-applications-development-sr-programmer-analyst](https://www.wearedevelopers.com/jobs/ext/4629104-applications-development-sr-programmer-analyst). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Applications Development Sr Programmer Analyst

- **Company:** Citi
- **Location:** Rutherford, NJ, United States
- **Experience:** Expert
- **Salary:** $31,460.0
- **Contract:** Permanent contract
- **Skills:** Adobe Flash, Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Information Engineering, Extract Transform Load (ETL), Database Applications, Relational Databases, Database Queries, JSON, Python (Programming Language), Machine Learning, Cloudera, Software Engineering, YAML, Google Cloud, Azure Data Factory, GitHub Copilot, ReactJS, Large Language Models, Prompt Engineering, Spring-boot, Agentic-AI, Fastapi, Build Management, Containerization, AngularJS, Pyspark, Kubernetes, Data Analytics, Apache Kafka, Front End Software Development, Data Pipelines, Docker, Databricks, Programming Languages, Microservices
- **Published:** November 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=dc8467b6a2f3bbfa

## About the Role

Required:

 * 5-8 years of overall experience in large-scale application development with recent experience in high-volume ELT/ETL processes using PySpark.
 * Experience with agentic AI development using YAML, JSON, FAST API or Spring boot, Google ADK, LLM integrations, including Devin.AI or Github Copilot, and integrating models via platforms like MCP using advanced prompt engineering.
 * Proven experience developing and automating microservice integrations to support data intensive applications.
 * Proficiency in at least one programming language commonly used for data analytics, engineering, such as Python or Scala.
 * Strong SQL skills and experience with various relational databases.
 * Excellent communication, collaboration, and problem-solving skills.

Preferred:

 * Practical experience applying AI/ML techniques to solve real-world business problems.
 * Familiarity with containerization technologies (e.g., Docker, Kubernetes).
 * Experience with cloud-based Big Data platforms (e.g., Cloudera, Databricks, AWS, Azure, GCP).
 * Experience in Front-end technologies like React, Angular
 * Experience in data engineering within the banking retail products domain (e.g., Cards, Mortgage, Deposits, Wealth Management).
 * Relevant industry certifications (e.g., AWS Certified Big Data - Specialty, Azure Data Engineer Associate).

Education:

 * Bachelor's degree/University degree or equivalent experience
 * Master's degree is a plus.

## Description

We are seeking a highly motivated and experienced Senior Engineer to join our Retail and Wealth Risk Engineering team under the Enterprise Risk Technology platform. This is an intermediate-level position responsible for designing, building, and maintaining robust, scalable applications and data pipelines & solutions for the secure and scalable deployment of AI agents, Big Data, Databrick and AI technologies. The ideal candidate is a high-impact individual with a passion for data, analytics, and problem-solving. You will play a key role in driving business engagement and growth by building the next generation of data and analytics platforms., * Design, develop, and maintain scalable applications and enterprise-grade AI agents , supporting ELT/ETL processes to handle large data volumes using the Python, FAST API, Java, SpringBoot, Microservices , PySpark, Kafka and Databricks ecosystem.

 * Build and Deploy GEN AI Agents using Googles ADK and Google Flash 2.5+ LLMs to support application automation supports and its deep insights, workflow support with HIL - Human in loop architecture.
 * Develop, deploy, and automate microservice integrations to support data-intensive applications, ensuring scalability, resilience, and maintainability using cloud native infrastructure and openshift or Kubernates architecture including CI/CD pipelines.
 * Integrate and leverage agentic AI tools (e.g., Devin.AI, Github Copilot) and platforms (e.g., MCP) through advanced prompt engineering to enhance development and operational efficiency.
 * Contribute to the continuous improvement of data engineering processes, standards, and best practices within the team.
 * Appropriately assess risk when business decisions are made, demonstrating consideration for the firm's reputation and safeguarding Citi, its clients, and assets by driving compliance with applicable laws, rules, and regulations.
 * Adhere to Policy, apply sound ethical judgment, and escalate, manage, and report control issues with transparency.