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SR Software Engineer – AI Enablement

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Onsite

SR Software Engineer – AI Enablement

Tential Solutions

SR Software Engineer – AI Enablement

Skills

Product ManagementGitMachine LearningAIAWSCompliance

1 month ago

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Important information


Contract type:

Freelance / Contract

Location:

Rockville, MD, USA

Work mode:

Onsite

Published on:

22 September 2026

What they need


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.

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