About Madison Logic:

　　Our team is reshaping B2B marketing and having fun in the process! As a truly global company, we take pride in the diverse backgrounds of our team. When joining Madison Logic, you are committing to giving 100% and always striving for more. Work with & learn from an incredible group of people who care about your success as much as they care about their own. Our team is at the heart of what we do and our success starts with you!

　　Remote work note: Please refer to the job posting detail to determine what (if any) remote work options apply to the specific job advertised. Not all positions are available for remote work or in all regions/countries. Where applicable, remote work must be conducted from your home office located in a jurisdiction in which Madison Logic has the legal right to operate. It requires availability and responsiveness on a full-time basis from a distraction free environment with access to high-speed internet. Please inquire for more details.

　　About the Role:

　　The AI Technical Product Strategist will assume a critical leadership role in guiding the development and execution of advanced AI-powered products and features. This role emphasizes expertise in data fluency and Large Language Models (LLMs). The AI Technical Product Strategist will collaborate with senior leadership, engineering, design, data science, and other business stakeholders to deliver innovative, data-driven solutions that establish Madison Logic as a true leader in the fast-evolving field of ABM intelligence. 

　　DISCOVER:

　　- Customer and user values and needs – Discovering customer and user values and needs for external products or user needs for internal products, with a particular focus on customer needs associated with the fast-evolving field of Artificial Intelligence and Large Language Models. 

　　- Market trends, problems and opportunities – Identifying problems and opportunities on the market which are not yet addressed, and which could be reliably solved leveraging ML’s proprietary data and AI models 

　　- Opportunity assessment – Evaluate the value of a product or business opportunity and prioritize correctly against a larger roadmap 

　　Validate solutions – Validation of devised solutions for customer or user needs or market problems with customers / users. 

　　- Competitive analysis – Monitoring and analyzing competitors for a concrete product or solution, to identify potential threats and advantages, particularly with regards to AI and LLM product offerings 

　　- Gap analysis - Analyzing and identifying our product’s or solution’s current performance and position and comparing it to desired one. 

　　DEFINE:

　　- Product vision – Defining the desired product state over a 3-5-year period. 

　　- Product strategy – Defining the plan that will drive the product vision. 

　　- Product or features or version launch / release – Defining releases of new products and features into rounded up values for the customer or user. 

　　- Product roadmap – Defining the product roadmap, a set of Product/Features/Version Releases overlaid on a time scale. 

　　- Go to market plan – Defining and delivering all elements of go-to-market plan as defined in product development process. 

　　- Success measurements and acceptance criteria – Defining the measurements and criteria that will be used to evaluate if a product or feature is successful. 

　　- Wireframes – Creating wireframes for visual products and features to communicate concepts and ideas. 

　　Functional specification – Defining which functions a new product or feature needs to have as per product development process. 

　　BUILD 

　　- Prioritize development and design work – Regularly prioritizing future work with development and design. 

　　- Remove roadblocks – Anticipate if execution of agreed work will be under status quo, blocked or will have uncertain status and work to gain clarity and progress with engineering leads. 

　　LAUNCH 

　　- Sales tools – Having tools for Sales ready at launch of new product or feature. 

　　- Product and feature metrics – Having product or feature metrics implemented and ready to be tracked at launch, including accuracy and reliability metrics measuring the quality of AI model recommendations 

　　- Education and training materials – Educating and training materials for all involved stakeholders of a product before the launch of a new feature or product, including AI education and training materials for both internal and external users 

　　- Business process alignment – Aligning processes of all departments and functions that support a product’s success before the launch of a new product or feature. 

　　- Public product documentation – Having ready product documentation for users and customers. 

　　- Early access program – Organize early access program (if applicable) to validate the release before public launch. 

　　SCALE 

　　- Product, solution or feature usage – Analysis of the usage patterns of a product, solution or feature and producing consequent actions. 

　　Product Responsibilities:Owning the data and AI product roadmap, shaping the strategy for what your team will focus on and how you’ll get there. Working in a cross functional team with Engineers, Designers, Data Engineers, Data Scientists, and other team members, bringing them along on the journey to solve data and AI problems together, collaboratively, in ways that unlock product value for other product domains and the rest of the business Prioritizing user research and developing an understanding of our users and clients at a deep level. Developing, owning, and delivering ideas from concept through design, development, UAT and deployment. Coordinating closely with senior leadership to ensure alignment with business objectives in the dynamic and evolving AI domain, aiming to understand business objectives and product, and ensuring the team has the right core metrics in place to deliver AI and data products that truly move the needle Assisting in development of internal and external training on AI and data across ML's product line. Becoming a subject matter expert on ML's products. 

　　AI Specific Responsibilities:AI & LLM Leadership: Lead the strategic direction for AI initiatives, including Large Language Models (LLMs), to align with the company's overarching objectives. Champion the strategic and practical application of Large Language Models across various product features and customer solutions. Data Productization: Serve as the organization's product authority on data models, data validation, and data-driven decision-making across multiple product lines, delivering new product vision and needle-moving improvement on existing products  Innovative Problem-Solving: Apply experience and insights in AI, data analytics, and LLMs to solve complex problems and seize new opportunities for customers, delivering reliable AI-powered intelligence that our clients can trust to help guide smart ABM campaign strategy planning. 

　　Qualifications:Minimum of 5+ years of experience as a Product Manager, with at least 3 years focused on AI, data-driven products, or LLMs, experience in B2B SAAS preferred. Advanced analytical and quantitative skills, with a deep understanding of data models, validation techniques, and statistical methods. Proven expertise in Large Language Models like GPT-3 or GPT-4. Demonstrated experience owning and delivering products end-to-end using Lean development methodologies Exceptional communication skills, capable of influencing senior-level stakeholders. Industry experience: AdTech or MarTech experience preferred but not essential Team structures: Experience working within cross functional team structures, partnering closely with Engineers and Designers, driving a collaborative and psychologically safe culture where everyone can share ideas. You have experience working in a team that ships at pace. Data driven: Able to measure the impact and results through insights, metrics and data. Communication: Exceptional communication and presentation skills. Growth mindset: Drive to learn and grow your Product Management skills. Action oriented: You have a strong bias for action and getting things done. Bachelor’s or Master’s degree in Computer Science, Business, Data Science, or a related field. 

　　Pay Transparency/Equity:

　　We are committed to paying our team equitably for their work, commensurate with their individual skills and experience.  Salary Range and additional compensation, including discretionary bonuses and incentive pay, are determined by a rigorous review process taking into account the experience, education, certifications and skills required for the specific role, equity with similarly situated team members, as well as employer-verified region-specific market data provided by an independent 3rd party partner.

　　We will provide more information about our perks & benefits upon request.

　　Who We Are:

　　 Our Vision: We empower B2B organizations globally to convert their best accounts faster

　　 Our Values: #TEAM     #OWNIT    #RESPECT     #EXCEL     #EMPOWER

　　Our Commitment to Diversity & Inclusion:

　　Madison Logic is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of sex, race, color, religion, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status.

　　Privacy Disclosure:

　　All of the information collected in this form and/or by your application by submission of your online profile is necessary and relevant to the performance of the job applied for. We will process the information provided by you in this form, your CV (including physical and online resume profiles), by the referees you have noted, and by the educational institutions with whom we may undertake to verify your qualifications with, in accordance with our privacy policy and for recruitment purposes only. 

　　For more information on how we process the information you have provided including relevant lawful bases (where relevant) please see our privacy policy which is available on our website (https://www.madisonlogic.com/privacy/).