AI Engineer

About Terminal AI

Terminal AI, a technology development and consulting firm focused on building and deploying practical AI systems, agentic workflows, and automations for businesses.

Terminal AI’s core philosophy is "Build what matters. Faster." Rather than acting as traditional consultants who just deliver strategy reports, they operate as hands-on builders who embed directly into a company's operations.

Core Offerings and Approach

• Forward-Deployed Engineers: Stationed embeds elite AI engineers directly into a client's team. These engineers engage with the messy realities of a company's business processes and start shipping production-grade code and working AI systems from week one, with no long ramp-up periods.
• 6-Week Sprints: They typically operate in focused, six-week engagements scoped to tackle a specific mission or build a specific system, ensuring fast delivery.
• 100% Capability Transfer: A key differentiator for Stationed is their focus on ownership. At the end of an engagement, they don't just hand over a product; they train the internal team and provide full documentation so the client's employees can maintain, own, and extend the AI systems themselves.
• Custom Agentic Systems: They specialize in building multi-step agent workflows, integrating Large Language Model (LLM) APIs, developing webhooks, and orchestrating cloud services to solve specific operational challenges and save time.
• Training & Labs: Alongside building infrastructure, they offer hands-on training programs (ranging from 4 to 6 weeks) on topics like prompt engineering and AI-accelerated development to upskill a company's existing workforce.

In short, Stationed AI acts as an accelerator for companies that want to integrate advanced AI workflows into their day-to-day operations but lack the specialized internal talent to build those tools from scratch.

About this Role

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

• Strong software engineering fundamentals in at least one modern language, preferably Python or JavaScript/TypeScript.
• 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 tradeoffs, 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 deploying AI systems inside real businesses.
• 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.