Senior Forward Deployed AI Engineer
J
JobgetherAgentic AI
Based in Brazil; work from BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- Spanish is considered an advantage, particularly for potential international collaboration. Fluency in additional languages is not required.
- Experience
- At least 2 years of hands-on experience implementing AI solutions in business environments and bringing Large Language Model (LLM)-based applications into real-world production use; at least 5 years of software development experience.
- Required Skills
- Node.jsTypeScriptLangChain
Requirements
- At least 2 years of hands-on experience implementing AI solutions in business environments and bringing LLM-based applications into production.
- At least 5 years of software development experience, including delivering and maintaining production code.
- Proven experience designing and building AI agents with platforms or frameworks such as LangChain, LangGraph, Vercel AI SDK, OpenAI Agents SDK, Claude Agent SDK, or equivalent technologies.
- Strong understanding of prompt engineering, tool calling, Retrieval-Augmented Generation (RAG), and response evaluation.
- Experience building or consuming Model Context Protocol (MCP) servers.
- Strong proficiency in TypeScript and Node.js, including developing, debugging, and maintaining integrations and applications.
- Practical knowledge of REST APIs, authentication mechanisms, and system-to-system integrations.
- Previous experience leading AI-focused training, enablement, or evangelization for business teams and non-technical users.
- Ability to understand business operations, engage non-technical managers, identify meaningful problems, and prioritize initiatives based on impact.
- Strong communication and stakeholder management skills, including explaining technical concepts without jargon and teaching others effectively.
- Ability to work across business functions, navigate ambiguity, and own initiatives from discovery through implementation and adoption.
Responsibilities
- Analyze business processes, performance indicators, and operational challenges to identify suitable opportunities for AI agents.
- Lead product discovery with business stakeholders and define problems, target users, outcomes, priorities, and success criteria.
- Design AI agents, specifying responsibilities, decision-making capabilities, data and system access, and human intervention points.
- Build and deploy end-to-end AI agent use cases, including integrations, tools, and MCP servers.
- Enable non-technical teams to create, use, and improve AI agents through workshops, learning materials, guidance, and ongoing support.
- Share implementation insights and concrete platform feedback with product managers.
- Monitor production agents for adoption, process improvements, response quality, operational effectiveness, and costs.
- Partner with AI engineers and software developers on complex integrations and custom engineering.
- Establish reusable practices to support AI adoption across business units and organizations.
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