Company Description

Data-Hat AI is building the next generation of intelligent decision systems for the fashion and retail ecosystem. We help global fashion brands and retailers optimize demand forecasting, inventory planning, replenishment, and omni-channel fulfilment using a combination of machine learning, deep learning, computer vision, and generative AI.

Our platform goes beyond dashboards and static models, we design agentic.

At Data-Hat AI, you’ll work at the intersection of real-world supply chain problems, cutting-edge AI, and high-impact business outcomes, with the freedom of a remote-first culture and the ambition of a product-led AI company.

Product:

 Orkestra AI (Agentic AI brain for retail) 

Location:

 Remote (India hours) 

Start:

 Part-time immediately; transition to full-time in future 

Level:

 Senior / Staff / Principal (hands-on leader)

Role Description

We are looking for a senior, experienced software leader who can execute end-to-end delivery of AI/ML/GenAI and agentic workflows for a fast-growing startup tackling large-scale problems in  retail, FMCG, fashion, and CPG . This is a hands-on role for someone who writes production code, ships reliably, and leads by doing.

You will work closely with a high-performing technical and business team and engage directly with customers across the US, UK, and Middle East. You must be able to think independently, earn trust quickly, communicate clearly, and drive outcomes in a remote-first environment.

Key Responsibilities

Product and Execution Leadership

• Own and drive delivery of critical product capabilities across AI/ML/GenAI workflows, from concept to production release.
• Convert ambiguous business problems (inventory distortion, forecasting, allocation, replenishment, pricing/markdown, supply chain) into clear technical plans and deliverables.
• Operate with strong judgment and urgency while maintaining engineering quality and scalability.

Hands-on Engineering

• Design, build, and maintain core backend services, APIs, data pipelines, and AI services that power Orkestra AI.
• Implement agentic workflows (multi-step reasoning, tool use, orchestration, memory, evaluation, guardrails) for real enterprise use cases.
• Build reliable LLM-enabled systems: prompt + tool design, RAG patterns, structured outputs, eval harnesses, latency and cost control.
• Productionize ML: feature pipelines, training/inference workflows, model monitoring, drift detection, and continuous improvement.

Architecture and Quality

• Define pragmatic architectures for distributed systems: modular services, event-driven pipelines, scalable inference, and secure enterprise deployment.
• Improve engineering rigor: CI/CD, code review standards, testing strategy, observability, incident response, and performance tuning.
• Establish repeatable delivery in a remote setting: sprints, milestones, documentation, decision logs, and reliable execution rhythms.

Customer and Stakeholder Engagement

• Work directly with customers and partners globally to understand business needs and translate them into product requirements.
• Lead technical discovery, solution design, and technical demos; communicate tradeoffs clearly to technical and non-technical stakeholders.
• Partner with product and business leadership to shape roadmap and ensure delivery matches customer value.

Required Qualifications

• 10+ years in software engineering with significant time in senior/staff/principal or technical leadership roles.
• Strong, proven experience building and shipping production systems using AI/ML and GenAI (not just prototypes).
• Demonstrated ability to build agentic workflows (or comparable orchestration systems) that interact with tools, data systems, and enterprise processes.
• Strong backend engineering skills (system design, APIs, distributed services, databases, performance, security).
• Deep experience with remote collaboration and modern software development methodologies.
• Excellent communication skills: can speak with customers, explain complex concepts simply, and write clear technical documentation.

Preferred Qualifications

• Experience with forecasting, allocation, replenishment, pricing/markdown optimization, supply chain analytics, or store-level demand signals.
• Experience building enterprise-grade RAG systems, knowledge graphs, or semantic search over structured + unstructured data.
• Familiarity with evaluation methodologies for GenAI systems (offline evals, regression suites, human-in-the-loop testing).
• Experience working with global enterprise customers (US/UK/Middle East), including security and deployment considerations.

Working Model & Commitment

• Part-time immediately  (hands-on delivery from week 1).
• Transition to  full-time  as the business scales and milestones are achieved.