Software Engineer - GenAI & Engineering Enablement

Job-ID29334766Reference26-01976Remote50% Remote Title: Software Engineer, GenAI Location : DC Metro Area Target Start Date : ASAP Type: contract Pay Rate : DOE We are seeking an accomplished Software Engineer with a strong interest in Generative AI to help identify, develop, and implement AI-driven solutions across the software development lifecycle (SDLC). This role combines hands-on software engineering with AI enablement. The ideal candidate has strong technical judgment, understands modern development practices, and can identify where AI and automation can meaningfully improve developer productivity and engineering workflows. In addition to building and prototyping solutions, this individual will serve as a technical advisor and educator, helping engineering teams adopt AI-enhanced development practices through demonstrations, training, workshops, documentation, and community-building initiatives. Key Responsibilities GenAI & Engineering Enablement Partner with software engineers, technical leaders, and internal users to identify opportunities for AI-driven improvements across the SDLC. Design, prototype, test, and implement AI-enabled development solutions and automation. Evaluate emerging GenAI tools and determine where they can provide meaningful value to engineering teams. Apply strong engineering and product judgment when determining what to automate and how solutions should be designed. Integrate AI capabilities into existing development workflows, tools, and processes. Identify and correct low-quality or inaccurate AI-generated code and technical content. Troubleshoot technical challenges related to AI tool adoption and integration. Serve as a technical advisor on AI development tools, implementation patterns, and best practices. Rapidly evaluate and incorporate new AI capabilities as technologies evolve. Technical Enablement & Content Development Develop technical enablement materials covering software development best practices, GenAI integration, development tools, processes, and standards. Create content for multiple learning formats, including instructor-led sessions, self-service resources, workshops, and hands-on labs. Partner with subject matter experts, engineers, architects, and technical leaders to develop and validate content. Gather requirements and identify engineering pain points, training needs, and automation opportunities. Maintain and continuously improve technical content as AI tools and engineering practices evolve. Build relationships across engineering teams to encourage adoption of new tools and development practices. Measure the effectiveness of enablement initiatives through feedback, assessments, adoption, and performance metrics. Training & Technical Presentations Lead technical training sessions, workshops, and demonstrations for engineering and technology audiences. Present to audiences ranging from small development teams to larger organizational groups. Demonstrate AI-enabled development tools, workflows, and engineering best practices. Translate complex technical concepts into clear, practical guidance for audiences with varying levels of technical expertise. Required Qualifications 5 years of hands-on software development experience. Strong understanding of the software development lifecycle, including Agile development, DevOps, CI/CD, Git/version control, testing strategies, and deployment practices. Hands-on programming experience and the technical depth to engage directly with software engineering teams. Experience using or integrating Generative AI and AI-assisted development tools into software engineering workflows. Understanding of AI-powered coding and development tools, such as Kiro or similar AI coding assistants. Ability to critically evaluate AI-generated code and content for accuracy, quality, security, and maintainability. Experience developing, prototyping, and implementing technical solutions in partnership with cross-functional teams. Strong understanding of modern development tools, cloud technologies, and deployment platforms. Advanced technical problem-solving and troubleshooting skills. Ability to gather requirements and translate engineering needs into practical solutions. Experience working in rapidly changing technical environments and evaluating emerging technologies. Communication & Collaboration Strong presentation and public-speaking skills, particularly with technical audiences. Ability to explain complex engineering and AI concepts clearly to engineers, business partners, and leadership. Strong written communication, technical documentation, and instructional-content development skills. Ability to influence and build relationships across teams without direct authority. Comfortable facilitating workshops, technical demonstrations, and hands-on learning sessions. Collaborative mindset with an emphasis on building solutions alongside engineering teams rather than simply documenting existing processes. Preferred Qualifications Experience with engineering enablement, developer productivity, internal developer platforms, or developer tooling. Experience designing or delivering technical training programs. Experience implementing AI-assisted development practices within an enterprise environment. Familiarity with cloud-based software architectures and modern DevOps practices. Experience working within a regulated or highly controlled technology environment. Demonstrated ability to rapidly learn and apply emerging technologies. Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline. Relevant cloud, DevOps, software development, or AI certifications are a plus. Ideal Candidate The ideal candidate is a hands-on engineer who is excited about the potential of Generative AI but approaches it with strong technical judgment. You understand that successful AI adoption requires more than introducing new tools—it requires identifying the right use cases, validating AI-generated outputs, integrating solutions into existing engineering workflows, and helping developers understand how to use these capabilities effectively. You are intellectually curious, comfortable experimenting with emerging technologies, and able to move quickly from idea to prototype. You are equally comfortable writing code, demonstrating a new AI-enabled workflow, collaborating with engineers and architects, and presenting technical concepts to a broader audience. 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