GenAI Engineer Specialist

Job Description:

Responsibilities

• Strategic Vision and Alignment: Craft and articulate a vision for GenAI as it specifically applies to the product engineering teams in alignment with the US Deloitte Technology GenAI strategy. Collaborate with diverse stakeholders, including product, engineering, experience, delivery, security, and infrastructure teams.
• Advocacy and Technology Roadmap: Advocate for, develop, and communicate the GenAI implementation approach to the product engineering teams. Ensure the organization is well-informed about objectives, KPIs, technology roadmaps, and progress.
• Craft Mastery and Objectives Realization: Define, measure, and drive the achievement of KPIs. Establish and evolve AI/ML/GenAI domain standards and best practices. Actively be hands-on with design, architecture, and code most of the time, contributing to team velocity, and be actively engaged with engineers across SSDLC. Review code, drive tech debt reduction, and experiment with new tech.
• Capability Evolution and Development: Mentor and develop engineers. Coach and develop skills in modern engineering practices, related to AI/ML/GenAI. Showcase learning and mastery by showcasing experiments internally, speaking at conferences, writing whitepapers or blogs, and leading R&D collaborations.
• Iterative Value Delivery: Embrace an iterative/incremental approach to product engineering. Apply a learning-forward approach to navigate complexity and uncertainty. Ensure alignment with customer and business goals through iterative steps and empirical evidence.
• Customer-Centric Problem Solving: Focus on addressing critical issues faced by customers and users. Align technical solutions with business objectives. Minimize unnecessary technical complexities and overengineering. Drive teams toward peak performance through continuous learning and improvement.

Qualification & Expeirnece

•  A bachelor’s degree in computer science, software engineering, or a related discipline. An advanced degree (e.g., MS) is preferred but not required. Experience is the most relevant factor.
•  Overall 16 years of experience with 12+ years of hands-on applied experience in AI/ML, with last 2 years focused on GenAI as well as technologies like OpenAI, Claude, Gemini, LangChain, Agents, Vector databases, and approaches like prompt engineering, fine-tuning, etc.
•  Strong understanding and experience in managing big data of various forms to generate insights and create intelligence.