Purpose of Position:
The AI Engineer is responsible for developing, testing, deploying, and supporting enterprise AI solutions that advance the Bank's Data & AI strategy. Reporting to the Head of Data & AI and working closely with the Lead AI Engineer, this role contributes to the design and implementation of AI agents, large language model (LLM) applications, retrieval solutions, integrations, and governance controls using Databricks and approved enterprise AI platforms.
This position provides an opportunity to work across data engineering, software development, AI governance, and business process optimization while developing expertise in generative AI, agentic architectures, and responsible AI practices within a regulated financial services environment.
Essential Job Functions:
AI Solution Development:
• Design, develop, test, and support AI-powered applications, copilots, and agent-based solutions using Python, Databricks, and approved enterprise AI platforms.
• Assist in building retrieval-augmented generation (RAG) solutions, workflow automations, and multi-agent architectures to support business objectives.
• Develop and maintain integrations between AI solutions and enterprise systems, databases, APIs, and business applications.
• Participate in prompt engineering, context management, tool integration, and agent orchestration activities.
Model Evaluation, Monitoring, and Optimization:
• Support the creation and maintenance of evaluation frameworks, test datasets, and benchmarking methodologies to measure AI performance.
• Assist in monitoring model quality, accuracy, safety, latency, and cost efficiency through dashboards and operational metrics.
• Troubleshoot AI application issues and contribute to performance tuning and continuous improvement initiatives.
• Participate in validation activities to ensure AI solutions meet business, regulatory, and governance requirements.
Data Engineering and Knowledge Management:
• Prepare, transform, and validate structured and unstructured data for AI and analytical applications.
• Collaborate with Data Engineering and Data Governance teams to ensure AI solutions utilize trusted, certified, and well-governed data sources.
• Support the development and maintenance of vectorized knowledge repositories and retrieval services.
• Contribute to data lineage, metadata, and documentation efforts supporting audit and governance requirements.
Governance, Security, and Compliance:
• Adhere to established standards for Responsible AI, information security, privacy, model governance, and change management.
• Support the documentation and evidence collection required for model reviews, audits, and regulatory examinations.
• Assist with monitoring guardrails related to AI safety, accuracy, traceability, observability, and operational effectiveness.
• Follow enterprise policies governing access controls, data handling, and model lifecycle management.
Collaboration and Continuous Learning:
• Partner with data engineers, BI engineers, analysts, and business stakeholders to deliver practical AI solutions.
• Support the development of dashboards and operational reporting that measure AI adoption, effectiveness, and business value.
• Research emerging AI technologies, tools, and engineering practices and share findings with the Data & AI team.
• Participate in peer reviews, technical discussions, and knowledge-sharing activities to support team growth and innovation.
• Perform other duties as directed.
Knowledge, Skills and Experience Requirements:
• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Information Systems, or a related field.
• 1-3 years of professional experience in software engineering, data engineering, machine learning, artificial intelligence, or a related technical discipline.
• Proficiency in Python and SQL.
• Experience working with cloud-based data platforms, preferably Databricks or similar technologies.
• Foundational knowledge of large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and AI application development.
• Strong analytical, problem-solving, and troubleshooting abilities.
• Effective verbal and written communication skills with the ability to document technical solutions clearly.
Preferred Qualifications:
• Experience with Databricks, Azure, Git, CI/CD pipelines, and API development.
• Familiarity with agentic AI frameworks such as LangGraph, LlamaIndex, Semantic Kernel, or comparable technologies.
• Exposure to AI governance, model evaluation methodologies, and responsible AI practices.
• Experience supporting dashboards, reporting solutions, or operational monitoring capabilities.
• Understanding of AI and Data Governance principles.
• Prior experience within financial services, banking, or another regulated industry.
Our job titles may span more than one career level. The starting base salary for this role is between $120,000.00 – $145,000.00. The actual base pay is dependent upon many factors, such as: training, transferrable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future.
Amalgamated Bank is an Equal Opportunity and Affirmative Action Employer, Minorities / Females / Individuals with Disability / Veterans. AmeriCorps, Peace Corps and other national service alumni are encouraged to apply. View our Pay Transparency Statement. Submission of a resume or any information regarding your qualifications does not constitute a promise or offer of employment. At Amalgamated Bank, we consider an applicant to be someone who has interviewed at least once, in person, with the hiring manager. Amalgamated Bank does not sponsor applicants for work visas.
Effective February 18, 2025, employees in office-based positions will be working a Hybrid work schedule consisting of three days or more, on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence. This Hybrid work model does not apply to, and daily in-person attendance is required for, the contact center, branch service roles, and general services where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance does not apply to roles that have been designated as “remote”.
Amalgamated Bank does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for the position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
Skills Required
- Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Information Systems, or a related field
- 1-3 years of professional experience in software engineering, data engineering, machine learning, artificial intelligence, or a related technical discipline
- Proficiency in Python and SQL
- Experience with cloud-based data platforms, preferably Databricks or similar technologies
- Foundational knowledge of large language models, prompt engineering, retrieval-augmented generation, and AI application development
- Strong analytical, problem-solving, and troubleshooting abilities
- Effective verbal and written communication skills, including the ability to document technical solutions clearly
- Experience with Databricks, Azure, Git, CI/CD pipelines, and API development
- Familiarity with agentic AI frameworks such as LangGraph, LlamaIndex, Semantic Kernel, or comparable technologies
- Exposure to AI governance, model evaluation methodologies, and responsible AI practices
- Experience supporting dashboards, reporting solutions, or operational monitoring capabilities
- Understanding of AI and data governance principles
- Prior experience within financial services, banking, or another regulated industry
