Tech Lead – Generative AI, Conversational Agents

Intervalor

Tech Lead managing generative AI projects for conversational agents within financial recovery solutions. Leading technical implementation from architecture to deployment with high autonomy and productivity.

Posted 7/3/2026full-timeSão Paulo • 🇧🇷 BrazilSeniorWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Technical Project Leadership: Take technical ownership of new projects, guiding implementation end-to-end based on Mutant's IAM framework playbooks.
Architecture and Development: Design the solution, configure agents, implement integrations (APIs/Webhooks), and work hands-on in Prompt Engineering and Context Engineering (RAG, etc.).
Lifecycle Management (End-to-End): Lead specification, design, quality testing (LLM QA), deployment, and post-launch performance monitoring of agents.
Client Interaction: Lead technical meetings with end clients to gather requirements, present solutions, align expectations, and troubleshoot.
Team Leadership: Provide technical guidance to specialists assigned to the project/operation, ensuring technical cohesion and smooth delivery.
AI-driven Productivity: Use AI tools extensively day-to-day to scale personal productivity, automate repetitive tasks, and accelerate development.

Requirements

What you’ll need

Proven experience with Generative AI / LLM projects applied to conversational solutions (text and voice).
Strong expertise in Prompt Engineering and Context Engineering (RAG architectures - Retrieval-Augmented Generation, embeddings, vector databases).
Coding ability for integrations and automations (e.g., Python, MCP, A2A, REST APIs, JSON).
Experience in testing methodologies, monitoring, and evaluating performance of language models (identifying hallucinations, latency, success rate).
Deep understanding of the fundamental concepts of Generative AI and its mathematical/statistical limitations.
Behavioral Skills (Soft Skills)
Assertive Communication: Ability to translate technical complexity for business clients and vice versa.
Autonomy and Self-management: Self-starter profile, able to navigate ambiguous scenarios and independently find solutions.
Hands-on and Lead by Example: Comfortable moving between strategic architectural vision and tactical technical execution.
Product/Journey Mindset: Empathy to understand the end user in critical journeys such as Sales, Support, and Collections, ensuring conversational flow and naturalness.
Previous experience in Customer Experience (CX) operations, contact centers, or support platforms.
Experience migrating legacy/deterministic chatbots to purely generative or hybrid architectures.

Benefits

Comp & perks

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Hard Skills & Tools

Generative AIPrompt EngineeringContext EngineeringPythonREST APIsJSONTesting MethodologiesPerformance MonitoringIntegrationsAutomation

Soft Skills

Assertive CommunicationAutonomySelf-managementHands-on LeadershipProduct Mindset