Web AI Engineer

About E2M E2M Solutions works as a trusted white-label partner for digital agencies. We support agencies with consistent and reliable delivery through services such as website design, web development, eCommerce, SEO, AI SEO, PPC, AI automation, and content writing.Founded on strong business ethics, we are an equal opportunity organization powered by 350+ experienced professionals, partnering with 400+ digital agencies across the US, UK, Canada, Europe, and Australia. At E2M, we value ownership, consistency, and people who are committed to doing meaningful work and growing together. If you’re someone who dreams big and has the gumption to make them come true, E2M has a place for you Role Overview As an Web AI Engineer who can design and build end-to-end AI automation solutions using LLMs, agents, tools, APIs, and MCP. The role focuses on building practical, production-ready AI systems and automation workflows rather than traditional ML model training. Key Responsibilities Design and build end-to-end AI automation and agentic architectures . Build workflows using LLMs, agents, tools, APIs, and MCP . Design and implement tools that allow AI systems to interact with applications and external services. Integrate LLM APIs and SDKs into production applications. Build multi-step workflows with proper context, state, validation, and error handling. Develop backend APIs and integrations required for AI-powered features. Debug and improve AI workflows for reliability, performance, and scalability. Take features from requirements and architecture through implementation and production. Required Skills & Qualifications 1–3 years of software engineering or AI application development experience. Strong understanding of: Agentic architecture Agentic loops Tool / function calling MCP Context engineering Prompt engineering Structured outputs Workflow orchestration Experience working with LLM APIs and SDKs. Strong understanding of REST APIs and system integrations. Good programming skills in Python, JavaScript/TypeScript, or similar languages. Ability to understand and design end-to-end system architecture . Strong debugging and problem-solving skills. Ability to work independently and take ownership of features. Good to Have Experience building MCP servers or custom AI tools. Experience with AI-assisted development workflows. Experience with Docker and cloud deployment. Exposure to Container Apps, Key Vault, or similar cloud services. What We Expect Ability to take an AI use case from concept → architecture → implementation → production . Strong understanding of how agents, tools, APIs, context, and application systems work together. Ability to learn new AI technologies and apply them quickly. Strong ownership and practical problem-solving ability.