Applications Engineer - Niche 3/Sr Developer & AI Innovation Lead

• We are looking for a forward-thinking technologist who sits at the intersection of modern software development and applied AI. This is not a traditional developer role — it is a transformation role. You will inherit a production Assortment Planning that Sport Planners rely on daily to build multi-season demand forecasts, manage style-level assortment plans, and support the Line Planning process across Footwear, Apparel, and Equipment. Today, the tool is Excel and VBA-based. Tomorrow, it needs to be something fundamentally better.
• Your mission is to reimagine how planners interact with Assortment and Demand data — reducing cycle times from weeks to hours, replacing manual macro-driven workflows with intelligent, AI-augmented experiences, and making the platform resilient enough to evolve as business needs change. You will lead this evolution end-to-end: from vision through architecture through delivery.

• Define and execute the technical vision for modernizing the LRAP platform, moving from Excel/VBA to a scalable, cloud-native architecture
• Identify high-impact opportunities to apply AI/ML — such as forecast generation, anomaly detection in plan inputs, intelligent defaults, and natural-language plan adjustments — and prioritize them against business value
• Serve as the team's AI thought leader: evaluate emerging tools, frameworks, and paradigms (LLMs, copilots, agentic workflows) and translate them into practical capabilities for Sport Planning

• Design and build the next-generation LRAP platform, enabling planners to construct and adjust multi-season demand forecasts at Mid-Level through Style/Geo granularity
• Architect data pipelines that replace manual CSV ingestion with automated, real-time data flows from upstream systems
• Build intuitive interfaces that let planners filter, slice, and manipulate plans (by Sport, Gender, Category, Season, Silhouette, Geo) with the speed and flexibility they have today — without the fragility of spreadsheet macros
• Ensure seamless version control, import/export, and plan comparison capabilities that planners depend on for seasonal continuity

• Partner directly with Sport Planners to understand their workflows, pain points, and decision-making processes — turning planner feedback into rapid iterations
• Collapse the feedback-to-deployment cycle: drive a culture where plan adjustments and tool enhancements are delivered in hours, not weeks
• Own the end-to-end delivery lifecycle: requirements, design, development, testing, deployment, and ongoing support
• Maintain and support the existing LRAP tool during the transition period, ensuring zero disruption to active planning cycles

• Mentor teammates on AI-first development practices and modern engineering approaches
• Advocate for and demonstrate how AI can augment (not replace) planner expertise — building trust through practical, visible results
• Contribute to broader technology strategy by sharing learnings and patterns that can scale across the Planning organization

• 5+ years of software development experience with strong proficiency in at least two of: Python, TypeScript/JavaScript, SQL, or cloud-native frameworks
• Demonstrated experience applying AI/ML in a product or business context — not just experimentation, but solutions that users depend on
• Proven ability to take a legacy tool or process and modernize it end-to-end (architecture, data layer, UX, deployment)
• Experience designing and building data-intensive applications — working with large, structured datasets, aggregation logic, and multi-dimensional planning grids
• Strong communication skills with the ability to translate between technical and business stakeholders; comfortable leading workshops, demos, and whiteboard sessions with non-technical planners
• Self-directed mindset: you can take ownership of a problem space, define the roadmap, and execute with minimal direction

• Working knowledge of demand planning, assortment planning, or merchandise financial planning processes — understanding how planners think about seasonal horizons, style-level forecasting, and geo-level allocation
• Experience with Excel/VBA automation tools and an appreciation for why users love spreadsheets (flexibility, speed, visibility) — and how to preserve those qualities in a modern platform
• Hands-on experience with LLMs, prompt engineering, AI agents, or copilot-style interfaces in an enterprise setting
• Familiarity with cloud data platforms (e.g., Snowflake, Databricks, BigQuery) and modern data orchestration tools
• Background in retail, consumer products, or supply chain technology

• Experience with forecasting models (statistical, ML-based) for demand or sales planning
• Familiarity with planning tools such as Anaplan, o9, Kinaxis, or similar
• Experience building tools that replaced or augmented spreadsheet-based workflows
• Background in sport or lifestyle retail

• Minimum required years of experience:= 5+ years of software development experience with strong proficiency in at least two of: Python, TypeScript/JavaScript, SQL, or cloud-native frameworks

• Demonstrated experience applying AI/ML in a product or business context — not just experimentation, but solutions that users depend on
• Proven ability to take a legacy tool or process and modernize it end-to-end (architecture, data layer, UX, deployment)
• Experience designing and building data-intensive applications — working with large, structured datasets, aggregation logic, and multi-dimensional planning grids

• Strong communication skills with the ability to translate between technical and business stakeholders; comfortable leading workshops, demos, and whiteboard sessions with non-technical planners
• Self-directed mindset: you can take ownership of a problem space, define the roadmap, and execute with minimal direction

• In 30 days: You have deep fluency in the current LRAP tool, have built relationships with key planners, and have delivered a modernization roadmap with a prioritized backlog
• In 2 months: Planners are using at least one AI-augmented capability that measurably reduces planning cycle time, and architecture for the next-generation platform is in place
• In 3–6 months: The team has shifted off legacy Excel/VBA workflows for core use cases, plan adjustments happen in hours instead of weeks, and the platform is positioned to scale across additional planning horizons and teams

Jaffer.s@sunrisesys.com