Bayantech

Product Marketing

• Own and execute go-to-market strategies for new products and major releases, from planning through post-launch
• Develop product positioning, messaging, value propositions, and buyer personas based on customer, market, and competitive insights
• Conduct market, customer, and competitive research to identify opportunities, trends, pain points, and product differentiation
• Partner with Product, Marketing, Sales, and Business Development teams to align messaging and support pipeline generation and product adoption
• Develop product marketing and sales enablement materials, including product briefs, one-pagers, landing pages, presentations, battlecards, and FAQs
• Plan and execute product campaigns, events, demos, webinars, newsletters, and other product marketing initiatives
• Own product launch communications and ensure consistent messaging across internal and external channels
• Gather customer and sales feedback to continuously improve product messaging, positioning, and adoption
• Track GTM, campaign, pipeline, and product adoption KPIs and use insights to improve performance

Product Marketing Manager – Part-time

AI Engineer

• Design and develop AI-powered solutions for natural language, speech, images, documents, and structured data
• Build and improve systems for search, question answering, summarization, content generation, classification, extraction, automation, and intelligent assistants
• Work with large language, speech, image, OCR, and multimodal models
• Develop AI pipelines processing text, audio, images, scanned documents, PDFs, forms, and tables
• Evaluate AI models for quality, speed, cost, reliability, scalability, and business fit
• Deploy AI services into production and integrate them with web, mobile, backend, and internal systems
• Improve AI system performance through testing, monitoring, optimization, and continuous iteration
• Collaborate with product, engineering, design, and business teams to deliver practical AI features
• Mentor engineers, review technical decisions, and contribute to AI architecture and best practices
• Research, compare, and select suitable AI models and tools
• Build useful, reliable, scalable AI features ready for real users
• Help reduce errors, improve quality, and turn AI experiments into production products