AI Engineer

Handoff
São Paulo, Brazil
Hybrid

Who this role is best for

Strong fit for engineers with AI agent experience who can navigate ambiguity and drive measurable outcomes in construction domain. Role demands technical ownership, client collaboration, and adaptability to real-world workflows.

Best fit for

  • Candidates comfortable with direct client interaction and embedding in enterprise teams
    — “you'll embed with each client's software and estimating teams, customize our deliverables to their exact standards.”
  • Individuals with a background in startup environments and a preference for high-ownership roles
    — “Proven experience working in a startup environment is a must.”

Things to consider

  • Role requires English proficiency for application and communication, which may limit non-native speakers.
    — “we will only consider applications submitted in English.”
  • Candidates must be prepared to handle ambiguity and switch between problems frequently.
    — “You’re comfortable with ambiguity and switching between problems, and you set your own agenda from the data.”

How to stand out

  • Highlight specific AI agent projects and quantify the impact on business metrics.
    — “You’ve owned an LLM-powered feature or agent in production and can point to a metric you moved.”
  • Showcase your ability to design and run experiments that differentiate real improvements from noise.
    — “You design experiments carefully and can tell a real improvement from noise.”
  • Emphasize practical experience with AI evaluation tools and observability frameworks.
    — “Experience building evals and using tracing tools such as LangSmith, Langfuse or similar.”
  • Demonstrate a deep understanding of how to align AI outputs with real-world customer needs.
    — “You care whether the output is right for the customer, not only whether the model call succeeded.”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • owning core AI metrics
  • running experiments on AI models
  • building evals and observability
  • improving customer outputs
  • shaping AI architecture
Typical background
software engineeringAI researchdata science

Skills & requirements

Required

Llm-powered Feature DevelopmentAI Metrics OwnershipExperiment DesignEvaluations And ObservabilityCustomer Problem DiagnosisAI Architecture ShapingCross-team CollaborationData-driven Decision Making

Preferred

PythonTypescript/nodeSQLCloud-based ArchitecturesLanggraph FrameworkLangsmithLangfuse

Stack & domain

PythonTypeScriptNodeSQLCloud-based ArchitecturesAmbiguityDirect Customer ContactAccountabilityAIConstructionSoftware Engineering

About the role

Original posting from Handoff via Lever

Why join us?

Handoff is the AI agent that runs a construction company. We help remodelers automate estimating, streamline operations, and win more work - backed by real-time cost data, intuitive design, and workflows that “speak contractor.” With over 10,000 monthly active users and $6B in annualized project volume already flowing through our platform, we’re becoming the trusted partner for the people who build our homes.

We are backed by $25M+ raised from Y Combinator, Initialized, and Greycroft. Our team is distributed across hubs in Austin, São Paulo, and Buenos Aires, and we are deeply focused on building intuitive, high-impact solutions that make a real difference for our users.

AI Engineer at Handoff

You’ll own how well Handoff’s AI works in production: its quality, speed and cost, across all of our products. When something degrades, you find out why, fix it and explain what happened.

Most of the work is experimentation. You’ll form a hypothesis, test it against evals and real traffic, and ship what the data supports.

What you'll do:

  • Own our core AI metrics and the dashboards and alerts behind them.
  • Run experiments on prompts, tools, context and models, from offline evals to controlled rollouts, and decide with data.
  • Build the evals and observability that let the whole team ship AI changes safely.
  • Improve what customers judge us on: accurate outputs, reliable actions and fast answers.
  • Shape the architecture of our agents as the product grows: how context, tools and memory scale.
  • Evaluate new models and providers as they are released, and lead migrations when they are worth it.
  • Work across Handoff’s products and teams, wherever AI quality, speed or cost needs attention.
  • Turn customer-reported AI problems into diagnosed causes and measurable fixes.
  • Share what you learn and raise the bar for AI engineering across the team.

About You:

  • You’ve owned an LLM-powered feature or agent in production and can point to a metric you moved.
  • You design experiments carefully and can tell a real improvement from noise.
  • 5+ years of software engineering experience, with strong Python and working knowledge of TypeScript/Node, SQL and cloud-based architectures.
  • Practical experience with agents: tool calling, context management, retrieval and structured outputs, ideally with a framework such as LangGraph.
  • Experience building evals and using tracing tools such as LangSmith, Langfuse or similar.
  • You’re comfortable with ambiguity and switching between problems, and you set your own agenda from the data.
  • You care whether the output is right for the customer, not only whether the model call succeeded.
  • Proven experience working in a startup environment is a must.

What we offer:

  • 💸 Competitive salary in USD
  • 💰 Attractive stock options
  • 🌴 Unlimited PTO
  • 🚛 Relocation allowance
  • 👨‍💻 Top-notch equipment
  • 🧳 Team offsites around the world!

We’re especially excited about engineers who enjoy turning emerging AI capabilities into useful, dependable experiences for real customers.

Please note that we will only consider applications submitted in English.

Source: Handoff careers (Lever)

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