AI SDLC Solutions Consultant

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

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