Lead software Engineer - AI / Full Stack

Job responsibilities

• Lead the design, development, and delivery of full stack AI-enabled applications and Conversational AI.
• Provide technical leadership across frontend, backend, API, database, and AI integration workstreams.
• Architect scalable, maintainable, and secure solutions using React, Python, Java, REST APIs, GraphQL, and database technologies.
• Guide the implementation of AI agents, AI workflows, RAG and intelligent automation capabilities.
• Establish and promote engineering best practices, including clean code, reusable components, automated testing, CI/CD, and design patterns.
• Drive integration with relational and non-relational databases, including SQL, Oracle, ElasticSearch and MongoDB.
• Collaborate with Agile SCRUM teams through sprint planning, backlog refinement, daily standups, demos, and retrospectives.
• Stay current with emerging AI, GenAI, full stack, and cloud-native engineering trends, and assess practical adoption opportunities.
• Experience with message queues, streaming platforms, pub/sub models, or event-driven architectures.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Required qualifications, capabilities, and skills

• Minimum of 5+ years of full stack application development experience.
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in REACT and one or more programming language(s)
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Practical cloud native experience ex. AWS
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices