Tech Lead - AI/ML, Comp Graphics

About Us: RocketFrog.ai is an AI Studio for Business, delivering cutting-edge AI solutions across Healthcare, Pharma, BFSI, Hi-Tech, Consumer Services, and other industries. We specialize in Machine Learning, Deep Learning, Agentic AI, and AI-driven Product Development to create real business impact. Ready to take a Rocket Leap with Science Role Overview: We are looking for a hands-on Tech Lead to design and deliver scalable AI-enabled software platforms. The ideal candidate should have strong technical leadership, system design, full-stack engineering, cloud, and AI/ML integration experience. This role requires someone who can guide engineering teams, make sound architecture decisions, and ensure production-grade delivery. Key Responsibilities Lead Technical Delivery: Own end-to-end technical delivery across application engineering, AI/ML integration, enterprise integrations, deployment, and production support.Design Scalable Architecture: Define system architecture, API contracts, data flows, database schemas, service boundaries, and integration patterns.Translate Business Problems into Technical Solutions: Work with business and product teams to understand requirements and convert them into practical, scalable technical designs.Integrate AI/ML Capabilities: Work with AI/ML teams to integrate models for product matching, forecasting, recommendation, planning, and decision-support workflows.Lead Application Engineering: Guide the development of web applications, dashboards, backend services, APIs, workflows, and data-driven user experiences.Integrate Enterprise Systems: Design and implement integrations with ERP, inventory, order management, production, warehouse, or other enterprise systems.Ensure Production Readiness: Own performance, scalability, security, observability, fault tolerance, CI/CD, and deployment readiness.Guide Engineering Teams: Mentor developers, review code, resolve technical blockers, and ensure architectural alignment across the team. Required Skills & Expertise: Technical Leadership: Ability to guide developers, review code, make architecture decisions, resolve technical ambiguity, and drive engineering execution.System Design: Strong understanding of API-first architecture, microservices, event-driven design, message queues, caching, and scalable application design.Full-Stack Application Development: Strong experience across frontend, backend, APIs, databases, and service-layer development using modern frameworks such as React, Node.js, FastAPI, Django, Flask, or equivalent.Programming: Strong hands-on skills in Python and JavaScript / TypeScript.Cloud Computing: Hands-on experience with AWS, Azure, or GCP, including deployment, storage, compute, networking, and managed services.Enterprise Integration: Experience integrating with ERP, CRM, inventory, supply chain, warehouse, or other enterprise platforms.Machine Learning Foundation: Good understanding of ML workflows including data preparation, feature engineering, model integration, evaluation, deployment, and monitoring.Image Processing / Computer Vision: Working knowledge of image processing, computer vision, visual matching, product image analysis, or similar areas.Mathematical & Analytical Thinking: Strong foundation in data structures, algorithms, probability, statistics, and analytical problem solving.DevOps & Production Engineering: Experience with Git, Docker, CI/CD pipelines, automated deployment, monitoring, logging, and reliability practices.Communication: Strong communication skills with the ability to explain technical concepts, trade-offs, and risks in simple language. Additional Skills Preferred: Computer Graphics / Visual Similarity: Exposure to computer graphics, shape analysis, visual similarity, product visualization, or feature extraction techniques.Fashion Industry Experience: Experience of applying AI, Image Processing, and Computer Graphics in the Fashion Industry. Planning / Optimization Exposure: Exposure to inventory optimization, allocation, matching, constraint-based planning, routing, or production planning algorithms.Domain Exposure: Experience in inventory management, demand forecasting, supply chain planning, production planning, merchandising, retail, manufacturing, or consumer goods.AI/ML Product Experience: Experience building AI/ML-powered platforms, decision-support systems, recommendation engines, or planning tools.AI / Agent Harness Engineering: Exposure to designing AI agent harnesses involving tool orchestration, guardrails, verification, observability, approval workflows, fallback handling, and human-in-the-loop controls.Data Engineering Awareness: Experience working with structured and unstructured data, SQL/NoSQL databases, ETL/ELT pipelines, and data quality issues.Startup / Product Engineering Experience: Experience working in fast-paced product engineering or startup-like environments. Required Background: Bachelors or Masters degree in Computer Science Abou