Forward Deployed Engineer AI - Sênior

Jobgether; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Fully remote (Brazil)

International collaboration

Exposure to cutting-edge AI platforms

Job summary

Jobgether seeks a result-driven professional to lead AI agent initiatives across business units. You will analyze processes, define problems with stakeholders, and design AI agents with clear human-in-the-loop points.

You will deploy end-to-end agent use cases on our platform and empower non-technical teams through practical training and concise materials. You will monitor adoption, performance, and costs while collaborating with AI engineers on complex integrations.

Qualifications

• 2+ years deploying AI solutions in business environments.
• 5+ years of software development experience with production code.
• Strong TypeScript/Node.js proficiency and API integrations.
• Experience building AI agents with established frameworks.
• Knowledge of prompt engineering and RAG techniques.

Responsibilities

• Analyze business processes and indicators to find AI value opportunities.
• Lead product discovery with stakeholders to define problems and outcomes.
• Collaborate with teams to design AI agents and human intervention points.
• Build and deploy end-to-end AI agent use cases on the platform.
• Enable non-technical teams to create and use AI agents through workshops and materials.
• Translate insights into concrete product feedback for managers.
• Monitor production agents for adoption, quality, and cost.
• Partner with AI engineers for complex integrations or custom solutions.
• Establish reusable practices to enable enterprise-wide AI adoption.

Skills

Business mindset

Product mindset

Communication skills

AI training & enablement

Applied AI experience

LLM techniques

MCP integrations

Software engineering

TypeScript/Node.js

APIs & system architecture

Autonomy

Tools

LangChain

LangGraph

Vercel AI SDK

OpenAI Agents SDK

Claude Agent SDK

Job description

Accountabilities:

• Analyze business processes, performance indicators, and operational challenges to identify opportunities where AI agents can deliver measurable value, while recognizing situations where alternative solutions are more appropriate.
• Lead product discovery with business stakeholders, defining the problem, target users, desired outcomes, priorities, and success criteria before selecting the appropriate technical approach.
• Collaborate with business teams to design AI agents, specifying their responsibilities, decision-making capabilities, data and system access, and the appropriate points for human intervention.
• Build and deploy initial end-to-end AI agent use cases on the existing platform, implementing the necessary integrations, tools, and Model Context Protocol (MCP) servers.
• Enable non-technical teams to independently create, use, and improve AI agents through practical workshops, concise learning materials, hands-on guidance, and ongoing support.
• Translate real-world implementation insights into actionable product feedback, communicating platform gaps, recurring challenges, and improvement opportunities to product managers with concrete examples.
• Monitor agents in production from both business and technical perspectives, tracking adoption, process improvements, response quality, operational effectiveness, and costs.
• Partner with AI engineers and software developers when use cases require deeper technical expertise, more complex integrations, or custom engineering solutions.
• Establish reusable practices and implementation approaches that support broader AI adoption across multiple business units and organizations.

Requirements:

• Business and product mindset: Ability to quickly understand business operations, engage confidently with non-technical managers, identify meaningful problems, prioritize initiatives based on impact, and challenge use cases that do not justify an AI agent.
• Communication and enablement: Strong communication and stakeholder management skills, with the ability to explain complex technical concepts without jargon, influence decision-making, and teach others effectively.
• AI training and adoption: Previous experience leading AI-focused training, enablement, or evangelization initiatives, particularly for business teams and non-technical users.
• Applied AI 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.
• AI agent development: Proven experience designing and building AI agents using platforms or frameworks such as LangChain, LangGraph, Vercel AI SDK, OpenAI Agents SDK, Claude Agent SDK, or equivalent technologies.
• LLM techniques and evaluation: Strong understanding of prompt engineering, tool calling, Retrieval-Augmented Generation (RAG), and response evaluation, including the ability to identify agent limitations and design reliable solutions around them.
• MCP and integrations: Experience building or consuming Model Context Protocol (MCP) servers to connect AI agents with enterprise data, tools, and systems.
• Software engineering: At least 5 years of software development experience, with demonstrated experience delivering and maintaining production code.
• TypeScript and Node.js: Strong proficiency in TypeScript/Node.js, with the ability to independently develop, debug, and maintain integrations and applications.
• APIs and system architecture: Practical knowledge of REST APIs, authentication mechanisms, and system-to-system integrations.
• Autonomy and adaptability: Comfortable navigating ambiguity, working across business functions, asking the right questions, and taking ownership of initiatives from discovery through implementation and adoption.
• Nice to have: Previous experience in product management, consulting, or solutions engineering, particularly in roles bridging business and technology; experience training non-technical teams in AI; and familiarity with Flutter and/or Ruby.
• Language skills: Spanish is considered an advantage, particularly for potential international collaboration. Fluency in additional languages is not required.

Benefits:

• Fully remote work model, offering flexibility to work from Brazil.
• Opportunities to collaborate with international teams and contribute to AI initiatives across different organizations.
• Exposure to agentic AI platforms, advanced LLM technologies, and real-world enterprise AI implementations.
• Opportunities to influence product strategy and help shape scalable AI adoption practices.
• A collaborative technology environment that encourages knowledge sharing, continuous learning, and professional development.
• Opportunities to contribute to innovative projects with meaningful business impact.
• Note: Specific salary details, healthcare coverage, and additional financial benefits were not provided in the original job description.