Lead AI Engineer

As a Lead AI Engineer, you will be responsible for designing and implementing AI-powered solutions using generative AI technologies to address real-world business challenges. Your role will involve leading the AI team, providing mentorship, and fostering a culture of innovation and collaboration. You will rapidly prototype and build AI applications by leveraging existing AI models, APIs, and services. Additionally, integrating multiple AI services and workflows to develop tailored solutions for clients will be a key part of your responsibilities. Key Responsibilities: - Lead the design and implementation of AI-powered solutions using generative AI technologies - Spearhead the AI team, providing leadership, mentorship, and fostering a culture of innovation - Rapidly prototype and build AI applications by leveraging existing AI models, APIs, and services - Integrate multiple AI services and workflows to develop comprehensive solutions for clients - Collaborate with cross-functional teams to ensure successful project delivery and alignment with business objectives - Stay updated with the latest advancements in AI and continuously incorporate new tools and technologies into solutions - Apply a growth-hacking mindset to identify opportunities where AI can add significant value - Communicate effectively with external partners, customers, and stakeholders to ensure clarity and alignment - Oversee the development and delivery of proof-of-concept demonstrations within the sales process - Manage project timelines, resources, and deliverables to ensure successful execution and client satisfaction Qualifications Required: - Proven experience as an AI Team Lead, AI Solutions Architect, or in a similar leadership role - Strong track record of building and deploying AI-powered applications using generative AI models - Experience with fine-tuning generative AI models (e.g., GPT-4, OpenAI APIs) for practical business solutions - Proficiency in integrating multiple AI services and APIs to create end-to-end solutions - Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and deploying AI solutions in production environments - Experience in leading teams, mentoring engineers, and managing full project lifecycles - Knowledge of MLOps practices and experience with maintaining AI applications post-deployment,