Junior AI Engineer

Key Responsibilities

• Aid in the design, development, and maintenance of AI-enabled business applications and workflow agents.
• Maintain data pipelines and application components using Python, SQL, and cloud-native technologies.
• Implement Generative AI solutions using Microsoft Azure AI Foundry, Snowflake Cortex, AWS Bedrock, Google Vertex AI, Databricks Mosaic AI, or similar enterprise AI platforms.
• Build and maintain Retrieval Augmented Generation (RAG) solutions and semantic search capabilities.
• Analyze, extract, and transform data from multiple enterprise sources to support AI and analytics use cases.
• Create REST APIs and application integrations.
• Integrate predictive models and AI-driven insights into business applications and dashboards.
• Participate in AI evaluation, tracing, and observability activities using tools like Arize AI Phoenix or similar platforms.
• Adhere to established data governance, security, and compliance standards.
• Create and maintain technical documentation, process flows, and development artifacts.
• Engage in Agile development activities, including sprint planning, daily stand-ups, backlog grooming, and retrospectives.
• Collaborate with senior engineers, AI architects, and business teams to achieve project objectives.

Required Skills

• Basic understanding of Generative AI concepts.
• Basic understanding of one of the following AI platforms: Microsoft Azure AI Foundry, Snowflake Cortex, AWS Bedrock, Google Vertex AI, Databricks Mosaic AI, or similar enterprise AI platforms.
• Experience with one or more modern data platforms such as Snowflake, Microsoft Fabric, or Databricks.
• Familiarity with REST APIs and enterprise application integration.
• Hands-on programming experience in Python and SQL.
• Understanding of machine learning.
• Basic knowledge of semantic search, embeddings, and RAG architectures.
• Exposure to AI evaluation and tracing tools such as Arize AI Phoenix, LangSmith, or equivalent platforms is preferred.
• Familiarity with data visualization tools such as Tableau or Power BI.
• Basic understanding of data governance and data quality principles.
• Familiarity with source control systems, CI/CD concepts, and Agile development methodologies.
• Experience using project management tools such as JIRA.

Position Requirements

• Minimum Education/Experience:
  • Bachelor’s degree (BA or BS) from an accredited college or university in Computer Science, Software Engineering, Data Science, Engineering, Mathematics, Information Systems, or a related field, plus a minimum of three (3) years of experience in software development, data engineering, analytics, or a related technical field.
  • Associate degree (AA or AS) in a related field plus a minimum of five (5) years of relevant experience.
  • High School Diploma or equivalent plus a minimum of seven (7) years of relevant experience.
• Preferred Experience: One (1) year of experience or exposure to Artificial Intelligence/Machine Learning (AI/ML) or Generative AI projects.
• Experience with cloud platforms, preferably Microsoft Azure.
• Financial services or credit union industry experience is desirable but not required.

Qualifications & Experience Required

• Knowledge of financial institutions and financial data, preferably credit union or retail banking related is a plus.
• Exposure to Azure OpenAI, Microsoft Azure AI Foundry, Snowflake.
• Familiarity with PgVector, Azure AI Search, Snowflake Cortex Search, Databricks Vector Search, Pinecone, Weaviate, OpenSearch, Elasticsearch, or similar vector search technologies, along with Enterprise Retrieval Augmented Generation (RAG) architectures.
• Experience with AI workflow agents and intelligent document processing.
• Exposure to AI governance, model monitoring, and responsible AI practices.
• Knowledge of Azure AI Document Intelligence is a plus.

Key Competencies

• Strong analytical and problem-solving skills.
• Ability to learn new technologies quickly and adapt to changing business needs.
• Good written and verbal communication skills.
• Ability to work independently while collaborating effectively within a team environment.
• Demonstrated initiative and curiosity in exploring AI technologies and solving business problems.
• Strong attention to detail and commitment to delivering high-quality solutions.