Data Scientist Python/R Sr

·        4+ years in Software Engineering, including experience with LLMs, Generative AI, or Agentic AI.

·        Strong Python skills; experience with TypeScript and/or Go.

·       Backend development and API integration (REST, gRPC), microservices, distributed systems, and scalable service architectures.

·        Experience with OpenAI, Anthropic, Gemini, or similar LLM platforms.

·        Knowledge of MCP, tool/function calling, AI gateways, and agent frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel).

·       Experience with RAG architectures, vector databases, and cloud technologies (AWS/GCP, Kubernetes, Terraform, Kafka). Experience designing scalable and distributed systems, including asynchronous processing, concurrency patterns, caching strategies, and performance optimization.

·       Strong understanding of software architecture and design patterns.

·       Experience building scalable, production-grade backend systems.

·       Knowledge of distributed architectures, event-driven systems, and asynchronous workflows.

·       Understanding of observability, monitoring, logging, and operational excellence.

·        Strong problem-solving and adaptability in fast-paced environments.

·        Excellent communication and collaboration skills with technical and non-technical stakeholders.

·        Experience with enterprise AI platforms and agent-based automation.

·        Knowledge of AI model optimization and fine-tuning.

·        Open-source AI/ML contributions and vendor management experience.

·       Experience optimizing latency, concurrency, caching strategies, and throughput in AI-powered applications.

·       Experience troubleshooting and optimizing multi-agent architectures, distributed workflows, and enterprise-scale platforms.

·       Design, develop, and maintain scalable software platforms, backend services, and Agentic AI and LLM-based solutions.

·       Build software and AI architectures, including distributed services, agent orchestration, RAG pipelines, and enterprise integrations.

·        Lead AI initiatives from PoC through production deployment and optimization.

·       Ensure reliability, performance, scalability, monitoring, governance, and security of software and AI systems.

·       Analyze and optimize latency, throughput, scalability, and reliability of AI-enabled applications and backend services.

·        Collaborate with business, engineering, and AI vendors to deliver enterprise AI solutions.

·       Evaluate emerging AI technologies and continuously improve platform scalability, reliability, and AI capabilities.

·        English: Advanced

·        Not specified

·        Hybrid,

·        Colombia, México.