Applied AI Engineer

DeepIntent•New York, NY

11d•$105,000 - $120,000•Remote

About The Position

DeepIntent is seeking an Applied AI Engineer to embed directly with their US commercial and operational teams. The role involves building a human and agentic “operating system” to power company operations. The engineer will act as a builder and problem-solver, translating day-to-day operational pain points into practical AI agent and automation solutions to increase efficiency. This position is ideal for someone passionate about applied AI, comfortable working across business and technical teams, and eager to make an immediate impact.

Requirements

Bachelors or Masters degree in Computer Science, Mathematics or Engineering
Hands-on experience with AI/LLM tools, including configuring and prompting models from providers such as OpenAI or Anthropic (i.e. you’ve successfully shipped a product or feature using Claude Code)
2+ years of hands-on software development experience, including internships, co-ops, or personal projects with deployed, real-world applications
Comfortable working with RESTful APIs, MCP servers, and integrating third-party services.
Scripting language (i.e. Python) proficiency — you can write scripts, build lightweight automations, and debug independently.
Understanding of prompt engineering best practices.
Naturally curious and proactive — you seek out problems, propose solutions, and don’t wait to be told what to build next.
Strong communicator who can work fluidly across business and engineering functions.
Comfortable with ambiguity — you can scope your own work and adapt as priorities shift.
Based in or able to work effectively within Eastern Time (EST).

Responsibilities

Design, build, and deploy AI agents that automate administrative and repetitive workflows across commercial operations.
Identify high-value automation opportunities by working directly with stakeholders to map processes and surface inefficiencies.
Develop solutions using LLMs (e.g., OpenAI, Anthropic Claude), workflow automation tools, RESTful APIs, and Python scripting.
Prototype, iterate, and ship working solutions quickly — moving from problem to deployed tool with minimal overhead.
Serve as the technical point of contact embedded within commercial and PMO teams, building strong working relationships with non-technical stakeholders.
Translate ambiguous business needs into clear technical requirements and executable solutions.
Communicate progress, surface blockers, and present solutions in a way that is accessible to both technical and non-technical audiences.
Create and maintain clear technical documentation for all tools, workflows, and integrations.
Monitor deployed solutions and proactively identify opportunities to improve reliability, performance, and adoption.