Responsibilities
Python expertise building and operating APIs/services, including:
Designing and implementing RESTful APIs (or GraphQL where relevant)
Python back-end frameworks such as FastAPI, Flask, or Django
Deployment, monitoring, and maintenance in cloud/server environments (CI/CD, logs, metrics, tracing)
Strong experience with data and persistence layers, including:
Relational databases (PostgreSQL/MySQL/etc.), schema design, indexing, and query optimization
Familiarity with vector search concepts and platforms (e.g., ChromaDB, Pinecone, Qdrant)
Knowledge of caching and performance patterns (e.g., Redis) is a plus
Solid understanding of software design principles (object-oriented design, modular architecture, design patterns) and building maintainable service-oriented systems
Awareness with testing methodologies (unit/integration tests, contract testing) and engineering quality practices
Awareness with cloud-based deployment (AWS, Azure, or GCP preferred), including containers/serverless where appropriate; infrastructure-as-code is a plus




Proficiency with JSON and distributed-systems integration patterns; XML familiarity is a plus where legacy integrations exist
Additional information
Experience working alongside data science, media, or ML teams
Understanding of generative AI engineering and LLM system design, including:
Practical knowledge of how LLMs behave (e.g., token limits/context windows, embeddings, latency/cost tradeoffs, hallucination risks)
Experience integrating LLM providers and AI APIs (e.g., OpenAI/Azure OpenAI/Anthropic, or open-source models), including tool/function calling patterns and MCP
Exposure to AI governance concepts such as bias awareness, explainability, or human-in-the-loop systems
Comfort using generative AI tools (e.g., ChatGPT, Gemini, Claude) for development, ideation, or research
Experience working with Docker containers and Kubernetes pods
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📌 Senior Back-End Engineer Ai (Bogotá)
🏢 Publicis Global Delivery
📍 Bogotá