Role Overview We are hiring a freelance web designer to take ownership of our landing page design projects. Your primary responsibility will be to create high-conversion, visually appealing landing pages in Figma. Secondarily, you’ll support the creation of web assets like icons, illustrations, and UI components that align with our brand. Key Responsibilities Design responsive landing pages from concept to high-fidelity prototypes in Figma (desktop and mobile) Create and manage reusable components, layout grids, and design systems for consistency across pages Collaborate with marketing and product teams to translate messaging into clear visual hierarchies and layout structures Support brand visuals through occasional illustrations, icons, and custom graphics Refresh and optimize existing pages for improved UX and visual consistency Prepare production-ready assets (SVG, PNG, JPG, PDF) with clear naming conventions and developer guidance Required Skills & Experience 3+ years experience designing landing pages and web interfaces Have a portfolio of designs to share Expert proficiency in Figma, including Auto Layout, components, and style libraries Strong understanding of responsive design, UX principles, and accessibility best practices Competence in visual design fundamentals: layout, color, typography, and branding Basic illustration and icon design skills (vector-based) Ability to work independently, iterate quickly, and manage deadlines Preferred Tools & Workflow Adobe Illustrator, Photoshop (for supporting graphic work) Familiarity with Procreate or similar tools for illustration (bonus) Zeplin or similar tools for developer handoff Sound knowledge of HTML/CSS for design-development alignment Deliverables Fully designed and responsive landing page prototypes in Figma Design system components and layout templates Optimized and export-ready web assets (icons, illustrations) Updated style guide for use across digital channels Show more Show less

Role Overview Build and deploy an end-to-end AI-driven SEO agent platform. You will own everything from prompt-engineering and RAG pipelines to CMS integration, staging environments, CI/CD, and a minimal frontend or plugin for demos. Key Responsibilities Design and implement LLM-powered agents (prompt flows, retrieval-augmented generation, embedding stores) using frameworks like LangChain, LlamaIndex (formerly GPT Index), or similar. Prototype and integrate vector-based retrieval with Pinecone, Weaviate, or Milvus. Build and secure REST APIs for WordPress, Shopify, headless CMS or React/Node.js platforms. Containerize services with Docker; orchestrate staging via Kubernetes or Terraform. Implement CI/CD pipelines (GitHub Actions, GitLab CI) with rollback and health-check gates. Scaffold lightweight frontend components or CMS plugins (React/Vue) to showcase agent capabilities. Automate SEO tasks on-page (metadata, schema injection), internal linking, and 404 recovery via code. Collaborate with prompt engineers and QA to validate agent outputs before production push. Required Experience 2+ years of software engineering with 2+ years in AI/ML or NLP projects. 1-3 years Python (FastAPI, Django) for API and agent development. Hands-on with LLM models (OpenAI GPT-4, Claude, or self-hosted LLaMA/Meta’s models) and fine-tuning pipelines. Experience with prompt frameworks: LangChain, LlamaIndex, Haystack, or equivalent. Proven RAG (Retrieval-Augmented Generation) implementation experience. Proficiency in Node.js and React (or Vue) for plugin/UI development. Strong background in Docker, Kubernetes (or Terraform), and CI/CD tools. Familiarity with CMS integration: WordPress REST API, Shopify Admin API, or headless CMS APIs. Solid prompt-engineering skills: few-shot, chain-of-thought, retrieval-augmented prompts. Knowledge of SEO best practices: metadata, JSON-LD schema, internal linking, and redirect management. Experience writing automated tests and health-check scripts for staging validations. Nice-to-Have Prior work on SEO automation, site-audit tooling, or custom CMS plugins. Experience deploying or fine-tuning open-source LLMs (e.g., LLaMA, Falcon, MPT). Exposure to Haystack, Retrieval QA stacks, or vector pipeline orchestration. Familiarity with monitoring/logging stacks (Prometheus, ELK, Grafana). Basic understanding of frontend styling (Tailwind, Material UI) for rapid prototyping. Apply if you can take full ownership of AI agent development and deployment, leveraging LangChain, style frameworks, and a range of LLMs, to deliver a working MVP in 4–6 weeks. Show more Show less