Looking for an AI SDLC Solutions Consultant to join our AI Adoption sub-stream in the Engineering Excellence Program. The ideal candidate has a strong technical background, deep understanding of delivery and engineering processes, and critical thinking skills. This role requires the ability to work directly with customers, run demos, and champion AI-driven engineering transformation across the entire SDLC. If you're adept at working with engineering leaders, driving measurable improvements in engineering outcomes, and accelerating AI adoption, we'd love to hear from you. Req# 777983296 Responsibilities Engages in pre-sales activities by identifying client engineering challenges, mapping AI solutions to specific engineering objectives, and developing proposals that highlight expected improvements in delivery speed, quality, and developer productivity Conducts demos and proofs-of-concept to showcase AI capabilities, addressing both technical feasibility and expected engineering impact for prospective clients Maintains relationships with potential and existing clients, proactively uncovering new opportunities for AI integrations across the SDLC that improve engineering efficiency and quality Collaborates with customers to understand engineering goals, challenges, and success metrics, ensuring AI solutions address real-world needs and align with the organization's engineering priorities Evaluates existing engineering processes to identify opportunities for AI-driven improvements in development, testing, and deployment, recommending strategic roadmaps that prioritize scalability and robustness Designs and prototypes AI-driven solutions (e.g., code review automation, test coverage optimization) by benchmarking platforms to determine fit-for-purpose integrations for the SDLC Conducts hands-on demos, workshops, and training sessions to showcase AI methodologies and best practices, accelerating adoption and reducing reliance on external support Establishes and tracks KPIs (e.g., cycle time, lead time, defect rate, AI adoption) to quantify AI's impact on engineering, presenting findings to stakeholders and guiding continuous improvement Develops playbooks, case studies, and technical documentation that encapsulate lessons learned, ensuring scalable and repeatable AI solutions within the broader Engineering Excellence Program Continuously researches and evaluates emerging AI technologies (e.g., large language models, generative AI), assessing potential and fit before piloting new features or solutions Requirements Hands-on experience with AI tools like Claude, Codex, GitHub Copilot, Microsoft Copilot, ChatGPT, or similar platforms, with a technical background to manage configurations and integrations Proven experience in client-facing roles, including delivering demos, proposals, workshops and identifying AI-driven solutions aligned with engineering goals Strong understanding of engineering processes (e.g., DevOps, CI/CD, testing) and the ability to recommend AI-driven optimizations Knowledge of data privacy regulations (e.g., GDPR, CCPA) and ethical AI practices Demonstrated skill in mapping AI solutions to engineering outcomes (e.g., delivery speed, quality, developer productivity), clearly illustrating the expected impact for clients Capable of presenting architectural decisions to both technical and non-technical audiences Skilled at establishing and tracking KPIs (e.g., cycle time, lead time, defect rates) to quantify AI adoption results and effectively communicate outcomes to stakeholders
