AI Engineer
AI Fund
- Brasil
- Permanente
- Período integral
- Own the AI Stack - Lead the architecture, development, and continual refinement of Freight Hero's AI capabilities, including data pipelines, model training, and real-time inference systems.
- Define the Strategic Vision - Establish the long-term roadmap for how AI can augment or automate broker workflows, from task automation to predictive analytics and agentic systems.
- Build and deploy AI-powered systems and tools-from internal operator assistants (e.g. summarization, internal copilots) to task-oriented agents (e.g. workflow routing, escalation flows) and real-time voice interfaces for interacting with external stakeholders. Leverage foundational models, fine-tuned LLMs, and open-source frameworks to support high-volume, high-reliability logistics use cases.
- Prototype, Validate, and Iterate - Rapidly develop MVPs, conduct real-world pilots, gather feedback, and fine-tune models and flows for reliability, and compliance with industry norms.
- Optimize for Human-in-the-Loop Performance - Design workflows that integrate seamlessly with Freight Hero's augmented operations team, empowering human agents while offloading repetitive tasks.
- Integrate with the Freight Ecosystem - Ensure your AI systems communicate effectively with TMS platforms, VOIP systems, CRMs, and broker operations tools, creating a seamless data and workflow layer.
- Build for Scale and Resilience - Architect scalable, cloud-native infrastructure that can handle concurrent sessions and asynchronous callbacks in real time.
- Collaborate Cross-Functionally - Work alongside operations, product, and engineering to align AI capabilities with business goals, SLA requirements, and user experience priorities.
- Stay Ahead of the Curve - Constantly evaluate advancements in AI, machine learning tooling, and infrastructure to keep Freight Hero on the cutting edge.
- English Proficiency - Strong written and verbal English communication skills required.
- LLM & Agentic Workflow Experience - Deep understanding of agentic workflow orchestration, prompt engineering, memory handling, and multi-turn conversation design using open-source or commercial stacks.
- Experience building AI-powered productivity tools-such as internal copilots, summarization services, or operator-facing assistants that integrate into daily workflows.
- Product Ownership Mindset - Ability to define what to build and why, balancing technical feasibility with operational impact and end-user delight.
- Startup Grit - Experience building from scratch in early-stage or high-velocity environments; you're comfortable wearing multiple hats and moving fast.
- System Design & Infrastructure - Proficient in designing scalable systems that integrate securely with cloud platforms (e.g., AWS, GCP, Azure) and internal operations tools.
- Human-Centric Automation - Passion for blending AI with human judgment-designing systems that enhance rather than replace frontline workers.
- Cross-Functional Collaboration - Strong communication skills and a bias toward action when aligning with business stakeholders and operations teams.
- Machine Learning Expertise - Hands-on experience with a variety of machine learning domains (e.g., natural language processing, predictive modeling, or computer vision).
- MLOps Experience - Prior experience with MLOps frameworks or building production-grade machine learning pipelines.
- Freight/Logistics Domain Familiarity - Prior experience or demonstrated interest in freight, logistics, or back-office automation.
- Accountability: an obligation or willingness to accept responsibility or to account for one's actions while doing so with the highest regard for integrity.
- Leadership: able to influence others to follow you and lead the team to a brighter future.
- Grit: able to stick with projects and work hard through good and bad times. High pain tolerance and can perform well under stress or pressure.
- Scrappy: Takes initiative and proactively gets things done with low resources, but doing creative things, begging, borrowing, and whatever is needed in an ambiguous environment or situation.
- Ownership Orientation: Demonstrated orientation of extreme ownership over all aspects of the company and extremely results-driven in nature.