Software Engineer – AI Prototyping and Demos

📍 Job Overview

Job Title: Software Engineer – AI Prototyping and Demos Company: GoodData Location: Prague, Czech Republic OR Brno, Czech Republic Job Type: FULL_TIME Category: Software Engineering / AI / Data Intelligence Date Posted: 2025-10-23 Experience Level: Mid-Senior (5+ years) Remote Status: Hybrid

🚀 Role Summary

• Develop and prototype cutting-edge AI-driven applications and demonstrations to showcase GoodData's AI vision in business intelligence and data analytics.
• Leverage expertise in Python and modern AI frameworks (e.g., OpenAI, Hugging Face) to rapidly build proof-of-concept solutions and interactive user experiences.
• Employ AI-assisted development techniques to accelerate the prototyping process and explore novel interaction patterns.
• Collaborate cross-functionally with Product Management and Marketing to effectively communicate the value of GoodData's AI initiatives.
• Continuously research and integrate emerging AI technologies to drive innovation and enhance platform capabilities.

📝 Enhancement Note: This role is focused on the "front-end" of AI innovation within GoodData, specifically translating complex AI concepts into tangible, demonstrable prototypes and demos. It requires a blend of strong software engineering fundamentals, deep AI/ML framework knowledge, and a creative flair for showcasing technological advancements. The "vibecoding" aspect suggests an experimental and rapid iteration approach, common in R&D or advanced prototyping teams.

📈 Primary Responsibilities

• Design, prototype, and build compelling demos and proof-of-concept applications that visualize and demonstrate GoodData's AI capabilities, including AI-powered BI, agentic analytics, and intelligent unstructured data processing.
• Rapidly iterate on prototypes to showcase novel AI-driven user experiences and advanced analytical functionalities, ensuring they align with the company's AI roadmap.
• Utilize creativity and in-depth knowledge of AI tools and frameworks to experiment with new ideas, develop prototypes, and deliver inspiring demonstrations for internal teams and external stakeholders.
• Apply AI-assisted development methodologies, such as "vibecoding" and prompt-based coding, to accelerate implementation, explore innovative interaction paradigms, and validate concepts efficiently.
• Partner closely with Product Managers and Product Marketing Managers to ensure prototypes effectively communicate GoodData’s evolving AI story and value proposition.
• Stay abreast of the AI team’s strategic roadmap and research initiatives, translating abstract concepts into tangible, working examples that highlight significant business value.
• Proactively explore, evaluate, and integrate emerging AI technologies, APIs, and vendor offerings to foster continuous innovation and optimize development efficiency.
• Uphold high technical standards through disciplined coding practices, thorough testing, and rigorous code reviews within a fast-paced prototyping environment.

📝 Enhancement Note: The responsibilities emphasize a hands-on, experimental approach to bringing AI concepts to life through software. The focus on "vibecoding" and "agentic analytics" points to a role at the forefront of AI application development, requiring adaptability and a willingness to explore uncharted territory. Collaboration with Product Management and Marketing is key to ensuring these prototypes translate into market-ready features.

🎓 Skills & Qualifications

Education:

• A Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field is typically expected, though equivalent practical experience will be strongly considered.

Experience:

• Minimum of 5 years of professional software engineering experience, with a significant portion dedicated to Python development and AI/ML integrations.
• Demonstrated experience in building applications, prototypes, or complex AI integrations.
• Proven ability to work effectively within agile development frameworks and utilize version control systems like Git.

Required Skills:

• 5+ years of Python development: Proven track record in building applications, prototypes, or AI integrations using Python.
• AI Frameworks & Tools: Hands-on experience with leading AI frameworks and tools such as OpenAI, Anthropic, Google Gemini, Hugging Face, LangChain, and LlamaIndex.
• AI-Assisted Development: Proficiency in AI-assisted development workflows, including prompt-based coding, copilot tools, and "vibecoding" methodologies.
• Frontend Development: Working knowledge of JavaScript/TypeScript and React for creating dynamic and interactive front-end interfaces.
• Software Development Fundamentals: Solid understanding of software development lifecycles, Git for version control, and agile methodologies.
• Collaboration & Communication: Excellent interpersonal and communication skills, with the ability to collaborate effectively in a dynamic, exploratory team environment.
• AI Passion & Curiosity: A genuine passion for AI innovation, keen curiosity about emerging technologies, and a strong drive for continuous learning and pushing technological boundaries.

Preferred Skills:

• Analytics/BI Integration: Experience integrating AI features directly into analytics or Business Intelligence products.
• AI Concepts: Understanding of prompt engineering, RAG (Retrieval-Augmented Generation), and agentic architectures.
• Backend Technologies: Experience with backend development using Kotlin, Node.js, or similar languages.
• System Architecture: Familiarity with API design principles, data pipeline construction, and cloud environments (e.g., AWS, Azure, GCP).
• Demo Development: Experience in developing interactive demos or visualizations specifically designed to simplify and communicate complex AI concepts.

📝 Enhancement Note: The emphasis on 5+ years of Python development and specific AI frameworks indicates a need for seasoned engineers. The "nice-to-have" skills suggest a preference for candidates who can bridge the gap between core AI development and its practical application within a data intelligence platform, highlighting a desire for well-rounded individuals who understand the product ecosystem.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase of at least two distinct AI-powered prototypes or proof-of-concept applications developed using Python and relevant AI frameworks.
• Demonstrated ability to rapidly iterate on ideas, with examples of early-stage concepts evolving into functional prototypes.
• Clear documentation or presentation materials explaining the problem addressed, the AI approach taken, and the business value demonstrated by the prototypes.
• Examples of interactive front-end components built with JavaScript/TypeScript and React that complement AI functionalities.
• Evidence of applying AI-assisted development techniques ("vibecoding") to accelerate development cycles or explore unique interaction patterns.

Process Documentation:

• For each portfolio project, provide a brief overview of the development workflow, including:
  • Conception and ideation phase.
  • Key technology stack choices and justifications.
  • Iterative development and testing process.
  • Methods used for showcasing AI capabilities effectively.
  • Lessons learned and potential future enhancements.

📝 Enhancement Note: Candidates are expected to present a portfolio that clearly demonstrates their ability to translate AI concepts into working software. The focus is on rapid prototyping and showcasing AI's impact, rather than solely on production-ready code. The "vibecoding" aspect suggests that efficiency and creativity in the development process itself are valued and should be highlighted.

💵 Compensation & Benefits

Salary Range:

• Based on industry benchmarks for a Software Engineer with 5+ years of experience in AI/Prototyping in Prague/Brno, Czech Republic, a competitive salary range is estimated to be between 90,000 CZK to 150,000 CZK gross per month. This range can vary based on the candidate's specific skill set, experience, and the final negotiation.

Benefits:

• Hybrid Work Model: Flexibility to balance on-site collaboration with remote work, fostering work-life integration.
• Professional Development: Opportunities for continuous learning, exploring emerging AI technologies, and attending relevant conferences or training.
• Innovation-Focused Environment: Be part of a team at the cutting edge of AI and data intelligence, working on impactful projects.
• Competitive Health and Wellness Programs: Comprehensive benefits package supporting employee well-being.
• Modern Technology Stack: Access to and utilization of the latest AI tools, frameworks, and development technologies.
• Collaborative Team Culture: Work in a supportive environment with opportunities for cross-functional collaboration and knowledge sharing.

Working Hours:

• Standard full-time working hours are expected, likely around 40 hours per week. The hybrid model offers flexibility in daily scheduling, with core hours for collaboration and team meetings.

📝 Enhancement Note: The salary range is an estimation based on typical compensation for a mid-senior software engineer specializing in AI in the Czech Republic. The "hybrid" work arrangement is confirmed, and the benefits are tailored to appeal to tech professionals focused on growth and innovation.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology / Data Intelligence / Artificial Intelligence Company Size: GoodData is a well-established company with a significant global presence, likely falling into the 500-1000+ employee range, indicating a robust organizational structure with dedicated teams for R&D, product, and marketing. Founded: GoodData was founded in 2007. This history suggests a company with a solid foundation in data analytics and a proven ability to adapt to evolving market trends, now focusing on the next wave of AI-driven intelligence.

Team Structure:

• The AI Prototyping team likely operates as a specialized unit within the broader engineering or R&D department.
• It will feature a mix of AI specialists, software engineers with AI expertise, and potentially product owners or UX designers focused on demo creation.
• Reporting lines would typically lead to an Engineering Lead, Head of AI, or CTO, with close collaboration across Product Management and Product Marketing.

Methodology:

• Agile & Iterative Development: Emphasizes rapid prototyping, continuous feedback loops, and iterative refinement of concepts.
• AI-First Approach: Prioritizes the integration and exploration of AI technologies to drive product innovation and user experience.
• Data-Informed Experimentation: Utilizes data and insights to guide the development and validation of AI prototypes.
• Collaborative Innovation: Fosters an environment where cross-functional teams work together to brainstorm, build, and test new ideas.

Company Website: https://www.gooddata.com

📝 Enhancement Note: GoodData's established history (founded 2007) combined with its current focus on "agentic AI for data intelligence" suggests a company that understands market evolution. The AI Prototyping team is likely a forward-thinking group within this structure, focused on R&D and demonstrating future product capabilities.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned at a mid-to-senior level within Software Engineering, specifically focused on AI prototyping. It's not a traditional "operations" role in the RevOps/SalesOps sense but requires operational excellence in development processes. Reporting Structure: The Software Engineer will likely report to an Engineering Manager or Lead within the AI/R&D division. Direct collaboration will occur with Product Managers and Product Marketing Managers, providing exposure to product strategy and market positioning. Operations Impact: While not a direct revenue-generating role, the impact is significant:

• Product Innovation: Prototypes developed here can directly influence future product roadmaps and features, driving competitive advantage.
• Market Perception: Compelling demos can shape market perception of GoodData's AI capabilities, influencing sales and customer adoption.
• Efficiency Gains: Successful AI integrations and "vibecoding" practices can lead to faster development cycles and more efficient prototyping processes.

Growth Opportunities:

• AI Specialization: Deepen expertise in specific AI domains (e.g., LLMs, agentic systems, RAG) and become a go-to expert.
• Technical Leadership: Transition into a technical lead role for AI prototyping projects, mentoring junior engineers and guiding technical direction.
• Product Influence: Gain significant influence over product strategy and future feature development through impactful prototyping.
• Cross-Functional Expertise: Develop a strong understanding of product management and marketing by working closely with those teams.
• Emerging Tech Exploration: Continuously learn and experiment with cutting-edge AI technologies, staying at the forefront of the field.

📝 Enhancement Note: This role offers a unique blend of deep technical work in AI and strategic product influence. Growth is geared towards becoming a specialized AI technologist with a strong understanding of how to translate innovation into tangible business value, rather than traditional operational management.

🌐 Work Environment

Office Type: Hybrid work environment, allowing for a mix of in-office collaboration and remote work. Office Location(s): Prague and Brno, Czech Republic. This offers candidates the choice of working from either of these major Czech tech hubs.

Workspace Context:

• Collaborative Spaces: In-office days are likely designed for brainstorming sessions, team meetings, and hands-on prototyping workshops, utilizing shared workspaces and meeting rooms.
• Technology Access: Expect access to robust development tools, high-performance computing resources for AI tasks, and modern collaboration software.
• Cross-functional Interaction: Opportunities to engage with engineers, product managers, and marketing professionals, fostering a holistic understanding of product development.

Work Schedule:

• Standard full-time hours (approx. 40 hours/week) with flexibility. The hybrid nature allows for a degree of autonomy in structuring the workday, balancing personal productivity with team synchronization needs.

📝 Enhancement Note: The hybrid model in well-established tech hubs like Prague and Brno suggests a professional yet flexible work environment. The focus on collaboration implies that in-office days are strategic for team synergy and knowledge transfer, particularly relevant for experimental AI prototyping.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of CV and portfolio, focusing on Python, AI framework experience, and relevant project examples.
• Technical Interview(s): Deep dive into Python coding skills, AI concepts, framework knowledge, and problem-solving abilities. Expect coding challenges and discussions on AI design patterns.
• Portfolio Presentation: A session dedicated to presenting 1-2 key prototypes from your portfolio. This will involve demonstrating functionality, explaining technical choices, and articulating the business impact or potential.
• "Vibecoding" / Prototyping Challenge: Potentially a take-home or live coding exercise focused on rapid prototyping of a small AI-driven feature or demo, evaluating speed, creativity, and technical execution.
• Behavioral & Cultural Fit Interview: Assessment of collaboration skills, passion for AI, adaptability, and alignment with GoodData's innovative culture. This may involve discussions with potential team members or hiring managers.

Portfolio Review Tips:

• Highlight AI Impact: Clearly articulate what problem your prototype solves and how AI is central to the solution. Quantify impact where possible (e.g., "reduced processing time by X%", "enabled new analysis of Y").
• Showcase "Vibecoding": If applicable, explain your rapid iteration process, how you used AI to speed up development, or how you explored multiple ideas quickly.
• Demonstrate Technical Breadth: Include examples showing proficiency in Python, relevant AI libraries, and front-end technologies (JS/React) if applicable.
• Storytelling is Key: Present your projects as narratives – the challenge, your innovative approach (especially AI-driven), the outcome, and lessons learned.
• Be Ready for Deep Dives: Anticipate technical questions about your choices, potential alternatives, and limitations of your prototypes.

Challenge Preparation:

• Practice Rapid Prototyping: Familiarize yourself with building small, functional demos quickly. Focus on core functionality over polish.
• AI Prompt Engineering: Be ready to discuss prompt design and optimization for specific tasks.
• "Vibecoding" Scenarios: Think about how you would use AI tools to accelerate common development tasks (e.g., generating boilerplate code, debugging, writing tests).
• Articulate Trade-offs: Be prepared to discuss the trade-offs between speed, accuracy, cost, and complexity in AI development.

📝 Enhancement Note: The interview process is heavily weighted towards practical application and demonstration of AI skills. The portfolio is critical, and candidates should prepare to not only showcase their work but also articulate the "why" and "how" behind their AI prototyping efforts, including the experimental "vibecoding" aspect.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (primary), JavaScript/TypeScript.
• AI Frameworks & Libraries: OpenAI, Anthropic, Google Gemini, Hugging Face, LangChain, LlamaIndex.
• Frontend Frameworks: React.
• Version Control: Git.
• Development Methodologies: Agile.

Analytics & Reporting:

• While not the primary focus, familiarity with data visualization tools and concepts might be beneficial for creating compelling demos.

CRM & Automation:

• Not directly relevant to this role, but understanding how prototypes might eventually integrate into a larger platform ecosystem is valuable.

📝 Enhancement Note: The core technical stack is clearly defined, emphasizing Python and a suite of modern AI tools. React for front-end is also a key requirement. Proficiency in these specific tools is paramount for success in this role.

👥 Team Culture & Values

Operations Values:

• Innovation & Experimentation: A strong drive to explore new AI technologies and push the boundaries of what's possible.
• Agility & Speed: Emphasis on rapid prototyping and iterative development to quickly validate ideas.
• Collaboration & Communication: Openness to sharing ideas, providing feedback, and working effectively across teams.
• Data-Driven Curiosity: A desire to understand how AI can unlock new insights and business value from data.
• Technical Excellence: Commitment to high-quality code and robust engineering practices, even in a prototyping environment.

Collaboration Style:

• Cross-functional Partnership: Close working relationships with Product Management and Product Marketing to ensure prototypes align with business goals and market needs.
• Open Feedback Loops: Encouraging constructive criticism and idea exchange within the AI and engineering teams.
• Knowledge Sharing: Proactive sharing of learnings from experiments, new technologies, and "vibecoding" insights.

📝 Enhancement Note: The culture is clearly geared towards innovation, speed, and collaboration, essential for a team focused on cutting-edge AI prototyping. Candidates should demonstrate alignment with these values, particularly a passion for AI and a proactive approach to learning and sharing.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Technological Evolution: Staying current with the incredibly fast pace of AI advancements and integrating new models/tools effectively.
• Balancing Speed and Quality: Delivering rapid prototypes while maintaining sufficient technical rigor and demonstrating clear value.
• Translating Abstract Concepts: Effectively communicating complex AI capabilities and their business impact through tangible demos.
• "Vibecoding" Nuances: Mastering and optimizing AI-assisted development workflows for maximum efficiency and creative output.

Learning & Development Opportunities:

• Deep AI Specialization: Opportunities to become an expert in specific AI domains like LLMs, agentic systems, or advanced RAG architectures.
• Exposure to Product Strategy: Understanding how R&D prototypes influence product roadmaps and market strategy.
• Cutting-Edge Technology: Hands-on experience with the latest AI models, frameworks, and development tools.
• Cross-functional Skill Development: Learning from Product and Marketing teams about user needs, market positioning, and effective communication.

📝 Enhancement Note: The primary challenges revolve around the dynamic nature of AI and the need to translate complex, rapidly evolving technology into understandable and valuable demonstrations. Growth is focused on deepening AI expertise and gaining strategic product insight.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you used AI to accelerate a software development task. What was the outcome?" (Focus on "vibecoding" examples).
• "Imagine we want to demo an agentic analytics assistant. What are the key AI components you'd focus on, and how would you prototype it quickly?" (Assess AI architecture and rapid prototyping thinking).
• "How do you balance the need for rapid prototyping with ensuring the underlying technology is sound and scalable for potential future implementation?" (Evaluate technical judgment and long-term thinking).

Company & Culture Questions:

• "What excites you most about GoodData's mission in agentic AI for data intelligence?" (Gauge genuine interest and understanding of the company's direction).
• "How do you stay updated with the latest advancements in AI, and how do you decide which new technologies are worth exploring?" (Assess continuous learning and strategic evaluation).
• "Describe your ideal collaborative environment for an AI prototyping team." (Understand fit with GoodData's culture).

Portfolio Presentation Strategy:

• Start with the 'Why': Clearly state the problem or opportunity each prototype addresses.
• Show, Don't Just Tell: If possible, provide a live demo or a well-recorded walkthrough.
• Explain the AI Magic: Detail how AI was used, which models/frameworks were employed, and why they were chosen.
• Highlight "Vibecoding" Wins: If relevant, explain how AI assistance sped up development or enabled new approaches.
• Discuss Business Value: Connect the prototype's capabilities to potential business impact or user benefits.
• Be Transparent About Limitations: Discuss what wasn't achieved and what the next steps would be.

📝 Enhancement Note: Interview preparation should focus on demonstrating practical AI application, rapid development skills, and a strong understanding of how AI translates to business value. The portfolio presentation is a key opportunity to showcase these abilities.

📌 Application Steps

To apply for this Software Engineer – AI Prototyping and Demos position:

• Submit your application through the provided link on Ashby.
• Curate Your Portfolio: Select 1-3 of your most impactful AI prototyping projects. Ensure they clearly demonstrate your Python skills, experience with AI frameworks (OpenAI, Hugging Face, etc.), and any use of "vibecoding" or rapid development techniques. Prepare to walk through these projects in detail.
• Tailor Your Resume: Highlight your experience with Python, AI frameworks, JavaScript/React, and any roles involving prototyping, R&D, or experimental development. Quantify achievements where possible, especially related to speed or innovation.
• Prepare for Technical Challenges: Review Python fundamentals, common AI concepts (LLMs, RAG, agents), and practice explaining technical trade-offs. Be ready for potential live coding or take-home tasks focused on rapid prototyping.
• Research GoodData’s AI Vision: Understand their focus on "agentic AI for data intelligence" and prepare to discuss how your skills and experience align with their mission.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

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