SR Software Engineer – AI Enablement

Senior Software Engineer – Enablement Team

Position Overview

Technically accomplished Software Engineer with a passion for GenAI technologies who will identify, develop, and implement AI-driven solutions within the software development lifecycle (SDLC). This role requires hands-on experience with GenAI tools, strong engineering judgment to identify high-value automation opportunities, and the ability to serve as a technical advisor on AI implementation.

The ideal candidate combines deep software engineering expertise with excellent communication and presentation skills to collaborate effectively with cross-functional teams and drive adoption of AI-enhanced development practices through training, workshops, and community building.

Core Responsibilities

AI Enablement & Solution Development

• Collaborate with the Enablement team, engineers, and customers to identify needs and develop AI-driven SDLC solutions.
• Prototype and validate solutions as AI tools and processes evolve throughout the year.
• Demonstrate strong engineering judgment by:
• Identifying which automations provide the most value.
• Determining the best approach to implementation.
• Balancing simplicity with sophistication.
• Clearly communicating decisions to technical and non-technical stakeholders.
• Apply problem-solving skills to address challenges related to AI tool adoption and integration.
• Bridge the gap between emerging AI capabilities and practical implementation within the SDLC.
• Rapidly incorporate new solutions into training materials and delivery programs.
• Serve as a technical advisor on AI tool selection, implementation patterns, and best practices.
  

Content Creation & Stakeholder Collaboration

• Develop instructional content covering:
• SDLC best practices
• AI integration
• Tools and platforms
• Processes and standards
• Deliver training across multiple formats, including:
• Self-service learning
• Instructor-led training
• Hands-on labs
• Identify and engage subject matter experts across technology teams to contribute to and validate content.
• Consult with technical leaders and engineers to understand pain points, training requirements, and solution opportunities.
• Build organizational relationships to gather input, secure buy-in, and encourage adoption.
• Maintain content relevance as SDLC practices, AI tools, and technologies evolve.
• Continuously improve training based on feedback, changing business needs, and emerging technologies.
• Track and measure training effectiveness through assessments, participant feedback, and performance metrics.
  

Training Delivery

• Facilitate instructor-led training sessions for both technical and non-technical audiences.
• Present to groups ranging from small teams to large organizational audiences.
• Adapt delivery style based on audience size, technical proficiency, and learning objectives.
• Provide technical demonstrations of tools, processes, and best practices.
  
  

Required Skills

Technical Knowledge & Development Background

• Strong SDLC expertise, including:
• Agile methodologies
• DevOps practices
• CI/CD pipelines
• Git/version control
• Testing strategies
• Deployment practices
• Developer background with hands-on software development experience and coding proficiency.
• Experience integrating AI into the SDLC, including AI-powered development tools (e.g., AWS Kiro CLI).
• Ability to identify and correct low-quality AI-generated content.
• Experience developing and implementing technical solutions in partnership with cross-functional teams.
• Strong understanding of development tools, cloud technologies, and deployment platforms.
• Advanced troubleshooting and problem-solving skills.
  

Instructional Design & Training

• Ability to rapidly update and evolve training content as tools, processes, and solutions change.
  
  

Communication & Interpersonal Skills

• Strong public speaking and presentation skills.
• Ability to explain complex technical concepts to engineers, customers, and leadership.
• Experience influencing stakeholders and driving adoption without direct authority.
• Excellent written communication and documentation skills.
• Technical credibility to engage effectively with engineering teams.
  
  

Collaboration & Enablement

• Experience partnering with enablement teams, engineering organizations, and end users.
• Ability to gather requirements and translate business needs into practical technical solutions.
• Experience with rapid prototyping and iterative solution development.
• Comfortable operating in fast-paced environments with evolving technologies.
• Collaborative mindset focused on co-creating solutions rather than merely documenting processes.
  
  

Personal Attributes

• Strong organizational and prioritization skills.
• Self-starter who thrives in ambiguous environments.
• Continuous learner with intellectual curiosity and technical fluency.
• Adaptable and resilient when managing feedback and shifting priorities.
• Agile problem solver capable of pivoting as new tools and technologies emerge.
  
  

Experience

Preferred Qualifications

• 5 years of software development experience with demonstrated SDLC expertise.
• Experience supporting enablement initiatives or internal developer platforms/tools.
• Experience in financial services or other regulated industries preferred.
• Demonstrated ability to learn and adopt new technologies quickly.
  
  

Education

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, or a related technical field.
• Relevant technical certifications related to SDLC tools or practices preferred.
  
  

Success Metrics

Success In This Role Will Be Measured By

• Training completion rates and participant engagement.
• Knowledge retention and practical application of learned concepts.
• Training and stakeholder feedback scores.
• Adoption of programs among new and existing employees.
• Contributions to AI enablement initiatives and successful solution implementations.
• Time-to-productivity improvements for developers.
• Content accuracy and speed of updates as technologies evolve.
• Stakeholder satisfaction with training quality, relevance, and enablement support.
• Consistent and timely delivery of training programs.
• Engineering team satisfaction with enablement partnerships and technical contributions.
  
  

Key Stakeholders

Reports To: Head of Engineering Enablement

Partners With

• Software engineering teams and architects
• DevOps, tooling, and platform engineering teams
• Security and compliance teams
• Product management
• Internal customers and SDLC tool users
• HR and Learning & Development teams
• AI/ML and Software Engineering Centers of Excellence
  
  

Supports

• Technology employees across the organization, from new hires to senior engineers.