Location: Hybrid — occasional client travel

Experience: Open range (mid to senior candidates encouraged to apply)

About DeepThink

DeepThink is an intelligence and automation platform that helps enterprises put their data to work in plain language. It connects to both unstructured content (documents, spreadsheets, presentations) and structured business systems (databases, APIs), then layers reasoning and automation on top — so teams can ask questions of their data, get analysis and visualizations on demand, and hand off repetitive or complex workflows to automated agents instead of doing them manually. The goal is to take work that used to require a request to a BI or analyst team, or hours of manual processing, and make it available directly, in natural language, to the people who need it.

About the Role

An AI Forward Deployed Engineer works directly with DeepThink's customers to design, build, and deploy AI-powered solutions that solve real business problems. It's a hybrid role that combines software engineering, AI/ML implementation, solution architecture, and customer engagement — taking a client's business requirements and turning them into a working, production-ready solution built on DeepThink's platform.

This is not a core platform-development role. You'll be the one on the ground with the client, from initial discovery through go-live.

Key Responsibilities

• Collaborate with customers, on-site and remotely, to understand business needs and identify opportunities where AI and automation can help.

• Design, build, and deploy AI applications and automated workflows using Python, LLMs, and agentic tools on DeepThink's platform, in collaboration with the core solution team

• Integrate solutions with existing systems, APIs, databases, and enterprise platforms — every client's environment is different, so comfort learning new systems is essential.

• Inventory and model each client's data sources, and structure that understanding into a clear, prioritized plan of what to build and in what order.

• Prototype, test, and iterate on solutions in a sandbox to ensure they're accurate, reliable, and deliver real business value before going live.

• Provide technical guidance, troubleshoot issues, and optimize deployed solutions post-launch.

• Own your engagements with a high degree of autonomy, while keeping leadership informed with clear visibility into progress and risks.

• Spend extended periods of time on site with customer, a large portion of which will be international customers globally

Key Skills

• Strong software engineering skills, particularly Python.

• Experience with LLMs, prompt engineering, and agentic or automation workflows.

• Solid understanding of APIs, databases (SQL), and system integration, with the range to work across varied enterprise tech stacks.

• Strong data modeling skills — able to walk into a client's environment and independently make sense of their systems and data.

• Excellent communication and customer-facing consulting skills; comfortable presenting to both technical and non-technical stakeholders.

• Highly organized, with the ability to bring structure and prioritization to loosely-defined or evolving environments.

• Willingness and ability to meet clients in person as needed, especially for local accounts.

Nice to Have

• Cloud platform experience (AWS, Azure, or GCP).

• Familiarity with agent/workflow orchestration frameworks (e.g., LangGraph).

• Prior experience in a client-facing, consulting, or implementation engineering role.

This role is ideal for engineers who enjoy combining deep technical expertise with direct customer collaboration to deliver impactful, real-world AI solutions.