Role Description In this role you will work alongside experienced AI/ML Engineers, Data Scientists, Designers and Product Managers to prototype and bring to MVP the GenAI/LMM components of new city services for residents. You will be our Gen AI expert in the team, your role will be a mix of hands-on and advisory: - Designing, developing and testing elements of the GenAI/LLM solution alongside other team members and city teams. - Providing technical advice and coaching to city teams, some of whom will be creating their own AI prototypes (e.g., code reviews, technical coaching and guidance). - Scoping: researching appropriate solutions and models, assessing feasibility, and ideating and designing suitable Gen AI/LLM solutions. - Contributing to workshops, advising on skills development and helping cities identify and address potential risks introduced through the application of GenAI/LLMs. Qualifications - Hands-on experience building LLM based applications (chatbots, agents, document extraction and summarisation, RAG based systems). - Strong programming skills, ideally in Python plus an LLM orchestration framework such as LangChain. - Experience with LLM safeguards and guardrails (e.g., managing hallucination risk and human-in-the-loop systems). - Experience working as part of an engineering team on a shared code base (e.g., using tools like Git, and documenting work that is in development). - Experience with API integration and data wrangling (e.g., data munging, data pipelines for ETL, data analysis). - Experience with rapid prototyping and MVP delivery — propensity to build and prototype, focus on progress and learning over perfection. - Ability to scope solutions based on existing data, skills, context constraints and ability to find pragmatic compromises and workarounds. - Comfortable working with uncertainty and incomplete information, communicating the assumptions made along the way. - Ability to work independently, solve problems that arise, use flexibility and comfortably to compromise. - Collaborative team player, with an ability to work well with other team members from different disciplines and communicate ongoing work, including flagging potential risks in a timely manner. - Ability to communicate and present technical ideas and concepts to non-technical stakeholders. - Ability to coach and support other technical and non-technical people in performing technical activities. - Ability to perform professional activities in Portuguese. Nice to have skills and experience - Broader experience working with data, such as: - Working with unstructured data (e.g., free text). - Working with or generating synthetic data. - Working with data in various languages. - Working with geospatial data, including satellite data. - Working with image data (for the purposes of computer vision), including video data. - Broader experience working with in city and/or local government. - Broader experience in Responsible AI. - Broader experience working in complex projects with competing objectives.

Role Description We are building an AI-driven video production system designed as an intelligent multi-agent orchestration layer capable of transforming raw ideas and references into fully structured video content. The system operates as a black-box creative engine for different types of users: - Professional video creators - Casual users - Creators of short narrative concepts Users provide an idea, references, or media fragments, and the system automatically orchestrates multiple AI agents responsible for: - Analysis - Scripting - Editing - Production of video content We are looking for an engineer who can design and implement multi-agent pipelines, orchestrate AI tools, and build intelligent workflows that combine video analysis, storytelling logic, and automated editing. This role sits at the intersection of AI systems architecture, creative tooling, and multimodal content generation. Responsibilities - AI Agent Architecture: - Design and implement the architecture of a multi-agent video editing system including agents responsible for: - Video analysis - Narrative generation - Editing orchestration - Production and output synthesis - Define system prompts, behavioral rules, and structured instructions for agents interacting within the pipeline. - Pipeline Orchestration (n8n): - Develop and maintain complex orchestration pipelines in n8n, including: - Multi-agent workflows - Tool-calling logic - Dynamic routing between tools and models - Context passing between agents - Pipelines must be capable of selecting the most appropriate models, tools, and strategies depending on the task. - Multimodal Data Processing: - Design robust pipelines for handling: - Video materials - Image assets - User text prompts - Structured metadata - Ensure proper data transformation and context transfer across the pipeline stages. - Tool & API Integration: - Integrate both external and internal APIs for multimodal generation and processing, including: - Image generation - Video generation - Speech synthesis - Audio generation - Video processing services - Rapidly evaluate available APIs and select the best quality tools and models for each task. - Model Orchestration & Optimization: - Tune and optimize model interactions, primarily based on Gemini models, including: - Prompt engineering - Structured outputs - Tool-calling workflows - Agent collaboration logic - Optimize pipelines for quality, reliability, and execution efficiency. - Future Architecture (RAG & Knowledge Systems): - Design systems that support: - Vector databases - Retrieval-augmented generation (RAG) - Memory and contextual reasoning between agents Requirements - AI Systems & Agent Architecture: - Strong experience building multi-agent systems, including: - Intent and sub-intent modeling - Agent orchestration - Agent communication and transport layers - Summarization pipelines - Context passing between agents - Workflow Orchestration: - Hands-on experience with n8n. - Agent tool-calling. - Experience designing complex automation pipelines is essential. - Programming: - Strong practical coding skills with vibe coding mindset: - Primary languages: Python, JavaScript. - Bonus experience: ComfyUI custom nodes, lightweight APIs (e.g., HuggingFace Spaces or inference endpoints). - Multimodal Tooling Knowledge: - Ability to quickly navigate API documentation and integrate tools for: - Image generation - Video generation - Speech synthesis - Audio generation - Multimodal analysis - You should know where and how to obtain the best generation quality for each modality. - Creative Thinking: - Strong sense of visual rhythm and composition. - Creative intuition and storytelling awareness. - Good taste in video structure and montage. - Ability to evaluate AI-generated output not only by metrics, but also by creative quality and narrative coherence. - Video & Media Processing: - Preferred experience with FFmpeg, video processing pipelines, image processing workflows. Nice to Have - Agentic Frameworks: - Deep understanding of frameworks such as LangGraph and LangChain for building complex cyclic state graphs and stateful agent systems. - Advanced RAG & Memory Management: - Experience designing long-term memory systems for agents, including mechanisms for storing and retrieving successful execution patterns or scenarios to improve future performance through experience-based retrieval. - Self-Correction & Reflection: - Experience building agents with feedback loops such as self-reflection, self-critique, or strategy correction, enabling them to verify their own actions and adapt execution logic dynamically. - Evaluation & Observability: - Experience with tools for monitoring, debugging, and evaluating agent chains and prompt behavior, such as LangSmith, Arize Phoenix, or Promptfoo, with the ability to identify logical failures, quality regressions, and orchestration bottlenecks. Ideal Candidate The ideal candidate is someone who naturally operates between engineering and creative production, capable of building systems that automate complex media workflows while preserving narrative coherence and aesthetic quality. You enjoy designing systems where AI agents collaborate to produce meaningful creative outputs. What’s next? If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider. We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.

Role Description Join us as an AI Engineer (ComfyUI) and become a driving force in scaling Zeely’s LLM initiatives and generative capabilities. We are looking for a specialist who will build a systematic approach to prompt creation and become a key player in the development of our AI platform. You will be responsible for creating scalable templates that work across hundreds of different products, as well as testing new generative models, identifying their use cases, and integrating them into Zeely’s pipelines. Your key responsibilities: - Design, build, and continuously optimize complex generative content pipelines across image, video, audio, and text formats. - Configure and fine-tune generative model parameters to achieve an optimal balance between quality, consistency, and performance. - Analyze, optimize, and improve existing workflows to increase stability, efficiency, and scalability in production environments. - Develop and maintain advanced ComfyUI pipelines, including working with custom nodes. - Proactively troubleshoot generation issues, quickly identifying root causes and implementing effective, long-term fixes. - Extend and evolve the capabilities of internal generative systems to support new use cases and product needs. - Collaborate closely with Product and Content teams to translate feature requirements into reliable, production-ready generative solutions. - Continuously research, benchmark, and test new models and tools, staying on top of market trends and emerging technologies, including: Flux, Nano Banana, OpenAI, Kling AI, Hailuo MiniMax, Veo 3, Runway, Pika Labs. Qualifications - 2+ years of hands-on experience in AI / Generative Systems Engineering, with a strong focus on prompt engineering within multi-step, production-grade generative pipelines. - Practical experience working with generative models across multiple modalities, including: text-to-text, text-to-image, text-to-audio, video-to-video, and others. - Strong expertise in ComfyUI as a core working environment, including developing custom nodes. - Deep understanding of the generative AI ecosystem, including model architectures, strengths/limitations, inference behavior, and rapid evaluation of new releases. - Practical experience integrating open-source models and tools into existing pipelines, including evaluation, optimization, and maintenance. - Experience designing and configuring LLM-based agents or automation flows (prompt logic, chaining, orchestration, tool usage). - High adaptability and strong learning velocity — ability to quickly test, validate, and adopt new models, tools, and techniques in a fast-moving AI landscape. - Strong communication skills, with the ability to collaborate effectively with Product, Content, and Engineering teams, and clearly explain technical constraints and trade-offs. Requirements - Nice to have: Experience with an intuitive “vibe coding” approach to content generation. Benefits - Work with cutting-edge technologies and contribute to building AI-powered tools. - Join a strong A-level team of experienced professionals who set a high bar and push each other to do better work. - Remote-first approach: work from anywhere, with access to our offices in Warsaw and Kyiv. - We take care of the essentials. Paid time off, sick leaves, and financial support with private entrepreneurship matters. - Regular performance reviews to ensure your growth is transparent and rewarded. Recruitment Process - Intro Call - Test Task - Final Interview - Reference check - Offer Send us your CV — we’d love to get to know you better!

• Build Strategic Partnerships • Identify and develop relationships with hardware vendors, system integrators, and solutions vendors, focused on the ai infrastructure arena. • Source and close new partner opportunities aligned with Hydra Host’s GPU and bare metal offerings • Drive Revenue Growth • Own partner pipeline from outreach, joint value proposition, expansion, and go-to-market activities. • Create scalable revenue channels through resellers, affiliates, and strategic alliances • AI Infrastructure Positioning • Clearly communicate Hydra Host’s value in GPU compute, low-latency networking, and high-performance bare metal • Align partner needs with infrastructure solutions (training clusters, inference scaling, etc.) • Expand Ecosystem • Build relationships with: OEM, System Integrators, and Ai-related ISVs • Data pipeline providers • Cloud & hybrid infrastructure players • Identify integration and co-selling opportunities • Partner Success & Retention • Ensure partners are successful and growing on Hydra Host • Track performance metrics and optimize partnerships over time • Own the Partner Portal with measurable results and partner KPIs.