[Hiring] AI Engineer @BotCity

Role Description

The AI Engineer will be responsible for designing and shipping AI-powered features directly into BotCity's product, owning the complete technical lifecycle from prototype to production as our first dedicated AI engineering hire. This person will establish production-grade AI engineering practices, drive measurable product impact through shipped features, and build the technical foundation that enables BotCity to integrate AI at scale. This role is built for someone who combines deep AI domain expertise with the software engineering discipline to turn research into reliable, maintainable product — someone who is energized by building from scratch, brings a strong portfolio of real AI work, and operates with full ownership in a fast-moving team. This position reports to the VP of Engineering.

Responsibilities

• Design, develop, and ship AI-powered features into BotCity's product, owning the full technical lifecycle from scoping to deployment and monitoring.
• Build production-ready AI components with proper engineering standards: clean code, testing, versioning, observability, and integration into existing infrastructure.
• Establish AI engineering practices for the team — evaluation frameworks, monitoring approaches, deployment patterns — that will scale as the AI footprint grows.
• Collaborate closely with product and engineering to identify where AI creates the most meaningful user value and translate those opportunities into technical proposals.
• Define and monitor technical health metrics for AI components in production, proactively identifying and resolving reliability or quality issues.
• Stay current with relevant AI research and tooling developments and proactively propose how new techniques can be applied to BotCity's product.
• Contribute to code reviews and technical discussions, helping elevate the engineering team's understanding of AI capabilities and limitations.
• Document AI components and decisions clearly to enable knowledge sharing and future maintainability.

Qualifications

• Master's degree or equivalent graduate-level education in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a closely related field.
• Proven, hands-on command (3+ years) of machine learning and AI engineering concepts.
• Prior experience integrating AI into a commercial software product (not standalone ML models).
• Strong software engineering fundamentals including but not limited to clean code, version control (Git), testing, CI/CD, and the ability to build maintainable, production-ready systems.
• Advanced Python proficiency.
• Hands-on experience with at least one major AI/ML framework or ecosystem (e.g., LangChain, LlamaIndex, HuggingFace, PyTorch, TensorFlow), including familiarity with AI agent frameworks and orchestration patterns, applied in a real project or production context.
• Deep, production-tested experience building Retrieval-Augmented Generation systems.
• Experience building and maintaining Model Context Protocol server infrastructure.
• Experience deploying AI models or components to production — including monitoring, versioning, and infrastructure basics (Docker, cloud platforms such as GCP or AWS).
• Demonstrable project work — GitHub repositories, published models, academic research, or shipped product features — that evidences AI domain mastery independent of years of professional experience.
• Experience with version control system tools such as Git and GitHub, CI/CD.
• Experience with Docker, Docker Compose and building multi-stage container images.
• Experience with at least one Vector Database (e.g. Pinecone, Weaviate, pgvector, MongoDB Atlas Vector, etc).
• Experience working with Atlassian Jira, MS Office/Excel, Google Suite, Notion.
• Ability to travel as needed to support events and meet the team.
• Portuguese - Fluent.
• English - Advanced.

Preferred Qualifications

• PhD in AI, ML, or related field.
• Experience working at or with enterprise software companies or automation platforms.
• Familiarity with AI agent frameworks, multi-agent orchestration, or agentic workflow patterns.
• Experience with computer vision, NLP, or domain-specific model adaptation.
• Active contribution to open-source AI projects, published technical writing, or participation in ML communities (Google Developer Expert, conference talks, etc).
• Experience with observability and monitoring tools for AI systems in production.
• Prior experience in an early-stage, high-growth, and fast-paced startup environment.