Vosyn

• Provide expert guidance on integrating ESG principles into core business strategies • Identify and assess ESG opportunities and potential risks across the organization • Design measurable social impact initiatives with clear, actionable metrics • Advise on stakeholder engagement strategies to align organizational goals with societal expectations • Create robust reporting mechanisms for ESG performance and progress • Support leadership in making data-driven ESG decisions • Develop recommendations for sustainable governance practices • Develop comprehensive ESG strategic frameworks tailored to Vosyn's unique organizational context

• Design and execute qualitative and quantitative research methods including interviews, surveys, diary studies, and usability testing. • Synthesize findings into clear insights and recommendations for the product team. • Collaborate with cross-functional teams to ensure research is effectively integrated into design and product development. • Help maintain a knowledge repository of research findings to support ongoing product decisions. • Advocate for the voice of the user throughout the product development lifecycle. • Stay informed about the latest user research methodologies and best practices.

• Connect to client systems — databases, APIs, CRMs, and other SaaS tools — and get data reliably out of and into them. • Extract, clean, transform, and move data so it is structured and usable by AI features, including retrieval and agentic workflows. • Build and maintain data pipelines that feed the Applied AI Engineer’s RAG and agent systems with current, correct data. • Use AI coding tools to accelerate integration work, while applying real engineering judgment to the bespoke, messy parts those tools handle poorly. • Handle the practical realities of client data: undocumented schemas, inconsistent formats, partial records, and access constraints. • Apply data-handling, security, and privacy best practices throughout, especially with client data. • Collaborate with the Builder and the Applied AI Engineer to ensure data flows cleanly end to end, and document integrations and pipelines in Notion so they are repeatable and maintainable.

• Build responsive web applications, internal tools, and landing pages primarily through AI coding tools such as Cursor, Lovable, Bolt, or v0. • Translate written briefs, feature requests, and client roadmaps into working, deployable software. • Prompt iteratively and refine AI-generated output to meet functional and design requirements. • Review, test, and debug AI-generated code to ensure it is correct, secure, and maintainable — not just “it ran once.” • Integrate front-end builds with the back-ends, agents, and retrieval services built by the Applied AI and Integration engineers so data and AI features flow end to end. • Recognize where vibecoding is the right tool and where a problem needs hand-written code or a teammate’s help, and escalate accordingly. • Deploy applications, gather feedback, and iterate quickly. • Document your work in Notion so others can pick it up.

• Design, build, and harden agentic workflows that plan and take actions reliably — and understand why agents fail (context loss, compounding errors, no feedback signal) and how to structure tasks so they succeed. • Build retrieval (RAG/search) pipelines that fetch the right client data and ground model outputs in it, integrated into core applications rather than demos. • Select the right model for each task — reasoning model vs. fast instruction model — and be able to justify the trade-off in latency, cost, and quality. • Engineer prompts and context structures appropriate to the model class, including knowing when reasoning models need framing rather than step-by-step hand-holding. • Write evaluations for AI features, because with non-deterministic models “it worked once” is not evidence that it works. • Connect AI tools to internal systems and data sources via APIs or MCP to power real client use cases. • Review and validate AI-generated code and automated workflows critically for correctness, security, and safety. • Collaborate with the Builder and the Integration & Data Engineer to deliver complete, working solutions, and document workflows, prompts, and integrations in Notion.

• Conduct comprehensive requirements gathering and process analysis across departments • Design scalable, robust automation solutions leveraging advanced technologies • Implement robotic process automation (RPA) and workflow automation • Develop and maintain detailed technical documentation • Monitor and optimize automation performance • Collaborate with cross-functional teams to drive technological innovation • Continuously explore emerging automation technologies and best practices

• Guide the team in evaluating and adopting optimal tech stacks for full-stack web development, considering both current and emerging technologies, with a focus on cross-platform compatibility • Provide expert-level mentorship on all aspects of cross-platform web application development, from front-end frameworks and state management to back-end architecture and API design • Lead architectural decisions and design patterns to optimize scalability, performance, maintainability, and security across the entire application stack • Advise on database selection and management strategies, including both SQL and NoSQL solutions • Share best practices for API design and development, including RESTful principles, versioning, and documentation • Offer guidance on implementing media streaming solutions using DASH and HLS • Provide expertise in implementing robust authentication and authorization mechanisms • Share insights on front-end performance optimization techniques and testing methodologies

• Provide expert-level advice and mentorship on the architecture, training, and production of text-to-speech (TTS) models • Guide the implementation of robust testing methodologies for TTS models using industry standards like MOS testing • Share expertise in distributed training, monitoring, and deployment of large-scale ML models on cloud platforms • Lead latency optimization initiatives in real-time systems for high-quality speech-to-speech conversion • Provide guidance on tuning TTS models for precise control over speech characteristics • Share in-depth knowledge of various TTS model architectures and waveform generation methods • Mentor the team on implementing advanced deep learning models for audio processing • Guide the development of transformer architectures for complex TTS model development

• Collaborate with researchers, engineers, and product owners to define product features and user journeys • Translate user needs and business requirements into intuitive wireframes, flows, and prototypes • Create and maintain high-fidelity design components in Figma • Participate in and lead design reviews, providing and incorporating feedback • Conduct design validation through usability testing and iterate on designs based on insights • Stay current with trends in product design, AI applications, and emerging technologies.

• Provide strategic guidance on cloud technologies, architectures, and real-time service implementation • Guide the team in evaluating and selecting appropriate cloud platforms and services, with a focus on solutions supporting real-time applications and low latency • Provide expert-level mentorship on cloud architecture design, implementation, and operation of scalable and resilient systems • Lead strategic decisions on cloud-native design patterns, microservices architectures, serverless computing, and container orchestration • Guide the implementation and management of Kubernetes clusters for containerized applications • Share expertise in designing, developing, and operating real-time services with minimal response times • Offer guidance on implementing cloud-based security solutions and compliance frameworks • Provide leadership in multi-cloud and hybrid cloud environment design • Evaluate and advise on technologies for building high-throughput, low-latency real-time data pipelines