Forward Deployed Engineer

Terminal; Miami (FL); On-site; USD 120,000 - 180,000; Full time

Job summary

Terminal seeks a Forward Deployed Engineer in Miami to sit inside customer environments, understand workflows, and turn messy problems into shipped AI systems. You will work with executives, operators, and engineers to design AI-native solutions and deliver measurable business outcomes.

This role blends engineering, product thinking, and customer communication, with in-office days in Wynwood and close collaboration with customer teams to scope, implement, and hand off production-ready AI systems.

Qualifications

• Experience building with APIs, databases, internal tools, workflow automation, or production software systems.
• Hands-on experience with AI/LLM tools, including OpenAI, Anthropic, LangChain, LangGraph, RAG systems, agents, evals, or similar frameworks.
• Ability to understand business processes and translate them into technical systems.
• Strong communication skills with both technical and non-technical stakeholders.
• Comfort working directly with customers and asking questions that uncover the real problem.
• Ability to move quickly from discovery to prototype to production.
• Strong judgment around trade-offs, reliability, security, data quality, and user experience.
• Clear written communication, including documentation, implementation plans, and customer updates.

Responsibilities

• Embed with customers to understand their business, workflows, data, tools, and operational bottlenecks.
• Translate ambiguous business problems into clear technical requirements, system designs, implementation plans, and success metrics.
• Build and deploy AI-powered workflows, agents, automations, integrations, dashboards, and internal tools.
• Work across APIs, databases, LLMs, retrieval systems, automation platforms, and customer software stacks.
• Prototype quickly, validate with users, and iterate based on real-world feedback.
• Partner with internal engineers to scope, prioritize, and ship production-ready systems.
• Lead customer-facing technical conversations, including discovery, calibration, implementation updates, and handoff.
• Identify where AI is useful, where it is not, and how to design systems that fit into human workflows.
• Document systems clearly so customers and internal teams can operate, maintain, and improve them.
• Act as the connective tissue between customer needs, business outcomes, and technical execution.

Skills

APIs & databases

AI/LLM tooling

Customer-facing communication

System design & prototyping

Discovery to production

Job description

We are building a new kind of AI deployment team: technical operators who can sit inside a customer’s business, understand how work actually happens, and turn messy operational problems into shipped AI systems.

As a Forward Deployed Engineer, you will work directly with customers, executives, operators, and internal engineering teams to identify high-leverage workflows, design AI-native solutions, and deploy production-grade systems that create measurable business outcomes.

This is not a pure software engineering role. It is also not a pure consulting role.

You need to be technical enough to build, debug, and ship real systems — and business-minded enough to understand the customer’s incentives, constraints, workflows, and definition of success.

The best people for this role are part engineer, part product thinker, part operator, and part customer translator.

The position is located in Miami and will require onsite meetings at our office in the Wynwood neighborhood. Mondays and Wednesdays are required in-office work days.

What You’ll Do

• Embed with customers to understand their business, workflows, data, tools, and operational bottlenecks.
• Translate ambiguous business problems into clear technical requirements, system designs, implementation plans, and success metrics.
• Build and deploy AI-powered workflows, agents, automations, integrations, dashboards, and internal tools.
• Work across APIs, databases, LLMs, retrieval systems, automation platforms, and customer software stacks.
• Prototype quickly, validate with users, and iterate based on real-world feedback.
• Partner with internal engineers to scope, prioritize, and ship production-ready systems.
• Lead customer-facing technical conversations, including discovery, calibration, implementation updates, and handoff.
• Identify where AI is useful, where it is not, and how to design systems that fit into human workflows.
• Document systems clearly so customers and internal teams can operate, maintain, and improve them.
• Act as the connective tissue between customer needs, business outcomes, and technical execution.

What You’ll Bring

• We are looking for people who can operate in ambiguity and create clarity.
• You should be comfortable walking into a customer environment where the problem is not fully defined, the data is messy, the workflow is undocumented, and the stakeholders are still figuring out what they actually need.
• You should be able to ask sharp questions, map the system, identify the bottleneck, and build the first useful version fast.
• You should have strong technical fundamentals, but you do not need to be a specialist in every part of the stack. What matters most is your ability to learn quickly, make sound technical decisions, and ship practical systems.

Required Skills

• Experience building with APIs, databases, internal tools, workflow automation, or production software systems.
• Hands‑on experience with AI/LLM tools, including OpenAI, Anthropic, LangChain, LangGraph, RAG systems, agents, evals, or similar frameworks.
• Ability to understand business processes and translate them into technical systems.
• Strong communication skills with both technical and non‑technical stakeholders.
• Comfort working directly with customers and asking questions that uncover the real problem.
• Ability to move quickly from discovery to prototype to production.
• Strong judgment around trade‑offs, reliability, security, data quality, and user experience.
• Clear written communication, including documentation, implementation plans, and customer updates.

Nice to Have

• Experience in consulting, solutions engineering, technical product management, startup operations, or customer‑facing engineering.
• Experience with CRM, sales, marketing, recruiting, support, finance, or operations workflows.
• Experience with cloud infrastructure, containers, orchestration, observability, or data pipelines.
• Experience building internal tools, dashboards, agents, or automation systems for non‑technical teams.
• Experience working in fast‑moving startup or client‑service environments.