AI Solution Software Engineer

Role Summary

The AI Solution Software Engineer (Staff/Principal) is responsible for designing, building, and deploying AI-native enterprise software platforms and applications that transform business workflows. This role demands not only technical excellence in full-stack engineering, AI Application architecture and development, and secure enterprise integration, but also a mindset where AI is the default tool for planning, ideation, and execution. You will work end-to-end—from exploration and prototyping through production deployment—delivering measurable business impact and championing AI-native ways of working.

Key Responsibilities

• Architect and develop AI-enabled applications leveraging LLMs, ML models, GenAI, RAG/GraphRAG, and NLP/NLM techniques
• Build full-stack web applications integrated with Azure AI services, ensuring secure, scalable, and resilient solutions
• Design and implement secure and managed data connectors and integrations for AI applications
• Ensure security, compliance, and stability of our AI solutions working in conjunction with cyber security, risk, and IAM teams
• Document architecture, workflows, and best practices; contribute to internal learning and knowledge sharing.
• Ensure production readiness: scalability, resiliency, monitoring, and operational handoff to IT and Support teams

Required Qualifications

• 8+ years in software engineering, with at least 3 years in applied AI solution delivery.
• Proven experience with Azure AI platform (OpenAI, AI Studio/Foundry, Cognitive Search), Azure Functions, and Claude Code.
• Strong proficiency in Python, TypeScript, and C#; experience with full-stack frameworks and RESTful APIs.
• Expertise in GitHub Enterprise, GitHub Copilot, VS Code, and CI/CD pipelines.
• Deep understanding of data security, governance, and compliance in enterprise environments.
• Knowledge of vector databases, data science models, and UX for AI-driven applications.
• Demonstrated self-learning and continuous upskilling in AI tools, models, and capabilities.
• Bachelor’s or Master’s degree in Computer Science or related field (or equivalent experience).

Preferred Qualifications

• Experience in knowledge-engineering and working with domain experts to build software that transforms and legacy processes.
• Experience working in high-compliance environments (Healthcare, Finance) and deep familiarity with security processes.
• Experience leading a team / working with outsourced engineers and influencing roadmaps.
• Experience with Dataverse, Fabric, and other similar technologies
• Experience developing AI solutions in financial or highly regulated industries.