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CI - Ssr. AI Engineer - 181 at Thaloz. We are seeking a highly skilled and motivated Senior AI Engineer to join our Continuous Integration (CI) team. The AI Engineer will play a pivotal role in designing, developing, and deploying AI-driven microservices that power our next-generation enterprise platform. This role is critical to advancing our AI capabilities by leveraging cutting-edge frameworks such as Langchain and LangGraph, and by implementing scalable, maintainable solutions within a microservice architecture. The ideal candidate will bring deep expertise in containerization, orchestration, and multi-agent systems, contributing to the robustness and efficiency of our AI infrastructure. This position offers an exciting opportunity to work at the intersection of AI innovation and cloud-native technologies, collaborating closely with cross-functional teams to drive continuous integration and deployment excellence.. Responsibilities. . Design, develop, and deploy AI-driven microservices using Python and advanced AI frameworks including Langchain and LangGraph.. . Architect and implement scalable multi-agent systems that enhance the intelligence and responsiveness of our enterprise platform.. . Utilize containerization technologies such as Docker to package AI microservices, ensuring consistency across development, testing, and production environments.. . Manage orchestration of containerized applications using Kubernetes, including programmatic handling of deployments through Kubernetes APIs.. . Collaborate with DevOps and platform teams to integrate AI microservices into continuous integration and continuous deployment (CI/CD) pipelines, ensuring rapid and reliable delivery.. . Implement and maintain MCP Reverse Proxy configurations to optimize routing, security, and load balancing for AI services within the enterprise deployment architecture.. . Contribute to the design and deployment of enterprise-grade AI solutions that align with organizational goals and compliance standards.. . Work closely with data scientists, software engineers, and product managers to translate AI research into production-ready services.. . Monitor, troubleshoot, and optimize AI microservices performance, scalability, and reliability in cloud environments.. . Participate in code reviews, knowledge sharing, and mentoring of junior engineers to foster a culture of technical excellence.. . Stay abreast of emerging AI technologies, container orchestration trends, and best practices to continuously improve the AI platform.. . . . Python. : Proficient in Python programming, with experience in developing AI applications and microservices. Ability to write clean, efficient, and maintainable code.. . . Langchain. : Expertise in Langchain framework for building AI applications that integrate language models with external data and tools.. . . LangGraph. : Experience with LangGraph for constructing and managing graph-based AI workflows and decision-making processes.. . . Microservice Architecture. : Strong understanding of microservice design principles, including service decomposition, API design, and inter-service communication.. . . Multi-agent Systems. : Proven experience in designing and deploying multi-agent AI systems that enable autonomous, collaborative, or competitive agent behaviors.. . . MCP Reverse Proxy. : Knowledge of MCP Reverse Proxy configurations and management to facilitate secure and efficient routing of AI microservices.. . . Enterprise Platform Deployment. : Familiarity with deploying AI solutions within enterprise-grade platforms, ensuring scalability, security, and compliance.. . . Docker and Kubernetes (K8s) Experience. : Hands-on experience with containerization using Docker and orchestration with Kubernetes, including deployment, scaling, and management of containerized AI services.. . Nice-to-Have Skills. . . Application-to-Application (A2A) Integration. : Experience integrating AI microservices with other enterprise applications to enable seamless data and process flows.. . . Advanced Embedding Strategies. : Knowledge of embedding techniques to represent complex data structures and semantic information for AI models.. . . Fine-Tuning. : Experience fine-tuning large language models or other AI models to improve performance on domain-specific tasks.. . . Evaluations. : Ability to design and conduct rigorous evaluations of AI models and systems to ensure quality and effectiveness.. . . Scaling with Tool Calling. : Familiarity with scaling AI workflows by orchestrating external tool calls and managing dependencies.. . . Programmatic Handling of Kubernetes Deployments through Kubernetes APIs. : Advanced skills in automating Kubernetes operations using APIs and custom controllers.. . . Sandboxed Environments for Ephemeral Code Execution. : Experience creating secure, isolated environments for running transient AI code safely.. . . Apache Kafka. : Knowledge of event streaming platforms like Apache Kafka to support event-driven architectures and real-time data processing.. . . Event Driven Architectures. : Understanding of designing AI systems that react to events asynchronously for improved responsiveness and scalability.. . . Caching Large Language Model Responses. : Techniques for caching AI model outputs to reduce latency and computational costs.. . . Large Language Model Memory. : Experience managing memory and context in large language models to enhance conversational AI capabilities.. . . Rule-Based Decision Making. : Ability to implement rule-based logic to complement AI-driven decision processes.. . . Graph-Based Decision Making. : Expertise in leveraging graph structures for complex decision-making and knowledge representation.. . . Swarm Architectures. : Familiarity with swarm intelligence concepts to coordinate multiple AI agents in distributed environments.. . Company Location: Brazil.