Software Engineer - AI

Pay Range: $73,600.00 - $98,141.00The Software Engineer – AI designs, develops, tests, deploys, and supports secure, scalable technology solutions that address business needs and improve customer and employee experiences. The role combines software engineering with emerging technology to build generative AI applications, intelligent agents, retrieval-augmented generation solutions, document intelligence capabilities, predictive models, APIs, integrations, and workflow automation. The engineer works across the full solution lifecycle—from requirements and architecture through deployment, monitoring, and continuous improvement—while applying responsible AI, data protection, security, model risk management, and human-review controls appropriate for a regulated financial institution. The role supports NBT’s Enterprise Technology strategy, which includes AI-enabled platforms such as Azure AI services, Microsoft Foundry, Copilot Studio, Microsoft Fabric, Freshservice and other approved enterprise platforms.

Education and Experience:

• A bachelor’s degree in computer science, software engineering, data science, mathematics, information systems, or a related discipline, or equivalent education and experience.
• Minimum of two years of professional software development experience.
• Experience developing applications or services using Python, C#/.NET, JavaScript or TypeScript, Node.js, REST APIs, and modern web frameworks.
• Experience with AI, machine learning, natural language processing, generative AI, or intelligent automation through professional work, applied projects, or formal education.
• Experience with SQL, relational databases, APIs, structured and unstructured data, and modern data platforms preferred.
• Experience with Azure AI services, Microsoft Foundry, Azure OpenAI, Azure Machine Learning, Copilot Studio, Microsoft Fabric, or comparable cloud AI platforms preferred.
• Experience with prompt engineering, retrieval-augmented generation, embeddings, vector search, AI agents, model evaluation, or model lifecycle management preferred.
• Experience working in a regulated industry, particularly financial services, preferred.
• Relevant Microsoft Azure, AI, software development, data, or DevOps certifications are preferred.

Skills and Abilities:

• Strong software engineering fundamentals, including modular design, source control, automated testing, code review, secure coding, API development, and continuous integration and deployment.
• Ability to design and build secure, maintainable AI-enabled applications, intelligent agents, integrations, and automation solutions.
• Understanding of generative AI concepts, including large and small language models, prompting, grounding, retrieval-augmented generation, model selection, context management, and agent orchestration.
• Ability to evaluate AI outputs for accuracy, relevance, bias, security, privacy, explainability, reliability, and fitness for the intended use.
• Familiarity with MLOps and GenAIOps practices, including versioning, deployment automation, evaluation, observability, performance monitoring, model or prompt changes, and lifecycle management.
• Understanding of responsible AI, data governance, model risk, human-in-the-loop controls, and secure handling of confidential or regulated information.
• Familiarity with Microsoft development tools, Azure DevOps or GitHub, repositories, agile delivery methods, infrastructure as code, and cloud-native solution patterns.
• Ability to collaborate with business partners, data engineers, cloud engineers, information security, enterprise risk, compliance, architecture, and other software developers to define and prioritize requirements.
• Knowledge of banking processes or a demonstrated ability to learn business processes, regulatory requirements, and related data.
• Strong analytical, troubleshooting, problem-solving, written communication, and verbal communication skills.
• Ability to explain AI capabilities, limitations, risks, and technical design decisions to both technical and nontechnical stakeholders.
• Ability to work independently, manage multiple initiatives, document solutions thoroughly, and adapt as AI technologies and standards evolve.

Additional Job Description

Tasks Performed:

• 35% — Solution Development: Design, develop, test, and maintain secure, modular, and reusable technology-enabled applications. Solutions may include generative AI applications, retrieval-augmented gen…