AI Productivity Engineer

We are looking for a highly skilled AI Productivity Engineer to lead the development and integration of AI-driven solutions, driving automation and efficiency across multiple business functions. In this role, you will play a crucial part in building scalable tools and workflows, optimizing internal processes, and fostering continuous productivity improvements. Your expertise will directly contribute to accelerating our GTM strategy, enhancing operational scalability, and shaping the future of AI adoption within our company.

The core responsibilities for the job include the following:

AI-Powered Automation and Operational Scaling:

• Lead the development and integration of cost-effective AI systems, leveraging LLMs and AI agents to optimize business operations, automate workflows, and improve customer support processes.
• Implement AI-based self-serve tools to reduce operational dependencies.
• Collaborate with product and engineering teams to integrate AI-driven automation into products, customer support, and internal operations.
• Identify and implement AI tools to enhance team productivity, GTM strategies, and business scalability.

AI Systems Architecture and Development:

• Set up evaluation frameworks for AI systems and drive experimentation to optimize performance.
• Lead the development and integration of AI agents for business automation (e. g., customer support, operations, GTM workflows).
• Rapidly prototype with AI tools, iterating from proof-of-concept (POC) to full-scale production deployment, aiming to minimize software development costs and maximize ROI.

Technical Leadership and Strategy:

• Assist in developing AI roadmaps and strategies to drive innovation and long-term efficiency.
• Ensure AI solutions align with business objectives, compliance standards, and scalability needs.
• Establish best practices for AI governance and continuously drive learning within the team.

Requirements:

• Experience in natural language processing (NLP) and conversational AI development.
• Familiarity with cloud platforms AWS / GCP / Azure.
• Strong problem-solving and analytical skills with a focus on performance optimization.
• Excellent communication skills to collaborate with cross-functional teams effectively.
• Experience with machine learning frameworks and tools.