Senior Software & AI Modernization Engineer

Role overview Modernize enterprise applications while keeping essential business operations reliable. This senior engineering role combines application development and support with phased legacy migration and production-ready AI solutions, from understanding existing systems and dependencies through design, deployment, and ongoing support.

Responsibilities - Assess legacy applications, including their business behavior, architecture, data, integrations, security dependencies, reports, and production relationships. - Plan controlled modernization phases that preserve required functionality while reducing technical debt and disruption. - Develop and maintain enterprise applications, APIs, services, integrations, and reusable components; investigate defects and production issues through to root cause. - Build AI-enabled tools, agents, and workflows using LLM platforms, approved enterprise data, structured prompting, and tool or function calling where appropriate. - Evaluate AI output quality and operational suitability; add validation and human review when decisions may be affected, along with logging, monitoring, access controls, and failure handling. - Support testing and releases across development, test, user acceptance, and production environments; document systems and deployments, define recovery approaches, and communicate status, estimates, risks, and blockers.

Requirements - Enterprise software development experience with JavaScript, TypeScript, Go, and Python. - Knowledge of modern application architecture, object-oriented development, legacy modernization, API design, REST services, SQL, and relational databases. - Experience with source control, CI/CD, deployment, testing, release management, secure development, and production troubleshooting. - Experience integrating third-party systems and services and collaborating with data, infrastructure, security, product, and support teams. - Practical AI application experience with several areas such as LLM APIs, agents, prompt design, tool calling, retrieval-augmented generation, embeddings, workflow automation, enterprise integration, or evaluation.

Nice to have - Microsoft or cloud environments such as Azure or AWS; healthcare or skilled nursing applications; large legacy conversions; database integration; Jenkins; or Power Platform and Copilot tools.