[Hiring] Applied AI Engineer @Dwelly

Role Description

We’re looking for an Applied AI Engineer to help build the agentic infrastructure that powers automation across Dwelly. Our growth model is acquisition, and our ability to scale depends on turning complex operational processes into reliable AI-driven and automated systems.

This is not an AI research role. You will be building AI systems that operate inside a real business and are expected to work reliably in production.

Key Responsibilities

• Agentic infrastructure:
  • Design and build the core primitives behind our agentic systems, including memory, context management, tool-calling, orchestration, and feedback loops.
  • Move us from one-off AI solutions toward reusable infrastructure where new workflows can be introduced quickly and with predictable reliability.
• Evaluation & observability:
  • Build the evaluation framework that allows us to understand how our agents perform and why they succeed or fail.
  • Make testing, tracing, debugging, and evaluating AI systems as fundamental to our engineering process as unit testing traditional software.
  • Develop the systems that allow us to confidently assess an agentic workflow before deploying it into production.
• Agentic development:
  • Push forward how we use LLMs to build software itself.
  • Create workflows where coding agents and specialized subagents can explore repositories, implement changes, review architecture, check conventions, run evaluations, and iterate with minimal human coordination.
  • Use agentic engineering workflows extensively in your own day-to-day development.
• Orchestration:
  • Design systems where specialized agents, tools, deterministic software, and humans work together effectively.
  • Understand when a problem should be solved with an LLM, when traditional software is the better solution, and when multiple coordinated agents can materially improve the outcome.
• Operational automation:
  • Act as the bridge between complex operational workflows and engineering.
  • Work closely with our operational and product teams to understand how work actually happens across acquired agencies, identify the highest-leverage opportunities for automation, and turn them into reliable production systems.
• Architectural influence:
  • Help define the architectural patterns we use for agentic systems as the company scales.
  • You will be an early core member of the team with significant influence over our technical approach, tooling, and engineering standards.

Qualifications

• Strong software engineering background with experience independently delivering complex systems from idea through to production.
• Hands-on experience building AI or agentic systems that have operated in production.
• Experience dealing with real-world AI challenges such as reliability, latency, context management, failure modes, evaluation, and observability.
• Strong understanding of agents, tool use, structured outputs, context management, orchestration, evaluation, and feedback loops.
• Advanced practical use of modern LLMs — understanding how to build reliable workflows around probabilistic systems.
• Experience using coding agents and agentic development workflows as part of your own engineering process.
• Experience decomposing complex engineering tasks across agents or specialized subagents and designing mechanisms for them to verify and improve their outputs.
• Strong architectural judgment and ability to decide when to use LLMs, deterministic software, human intervention, or a combination of approaches.
• Experience with TypeScript / Node.js, or strong experience building AI systems in Python with the ability and willingness to apply that knowledge in a TypeScript-first environment.
• High autonomy, ownership, and comfort making decisions under ambiguity.
• Strong product judgment and ability to connect technical decisions to operational and business outcomes.
• Strong communication skills and fluency in English.
• Startup mentality: resilience, adaptability, and ability to thrive in a fast-paced environment.

Requirements

• For this role, AI experience does not mean using ChatGPT to generate snippets of code.
• It does not mean adding a single LLM API call to an application.
• It does not mean building a prompt wrapper and calling it an agent.
• It does not mean blindly accepting whatever a coding agent generates.
• We are looking for engineers who think in terms of agents, tools, context, orchestration, evaluation, feedback loops, and human-machine collaboration.

What Success Looks Like

• Reliability: We can deploy a new agentic workflow and understand how it will perform before it reaches production because we have robust evaluation and observability systems in place.
• Speed: Integrating processes from newly acquired agencies takes days rather than weeks because we have a standardized library of reusable agentic primitives.
• Efficiency: A significant amount of repetitive operational work has been automated, allowing our teams to focus on the areas where human judgment and interaction create the most value.
• Engineering leverage: Agentic development workflows materially increase the speed and quality at which our engineering team can build, test, and evolve software.

Technology Stack

• TypeScript (Primary)
• Node.js
• PostgreSQL
• LLM Orchestration
• Agentic Workflows

Benefits

• The role is fully remote, providing flexibility and enabling seamless collaboration with our geographically distributed team.
• Competitive salary with the potential for equity options based on performance, recognizing exceptional contributions to our integration success.