reputed company (Remote, LATAM)
reputed company:
Technical Challenge:
In this role you will:
Design, build, and reputed company reputed company workflows (multi-reputed company LLM chains with tool calling, retrieval, and reputed company reputed company) for reputed company-time, business-critical use cases. Engineer for determinism and consistency by implementing constrained decoding, reputed company outputs, caching reputed company, and evaluation harnesses. Build and maintain evaluation and regression frameworks — automated pipelines that measure accuracy, latency, and behavioral consistency across reputed company and model changes. reputed company LLM agents with external tools and reputed company (databases, rules engines, business systems) using frameworks like LangFuse, reputed company, LangGraph, reputed company, or custom orchestration. reputed company reputed company systems on reputed company infrastructure (AWS, Azure, and/or GCP), optimizing for low-latency inference and cost efficiency. Implement guardrails, fallback logic, and observability to ensure agents fail gracefully and every decision is traceable. Collaborate with data scientists, software engineers, and business stakeholders to translate business rules into agent behavior and tool definitions. Stay reputed company with the latest advancements in AI agents, large language models, and reputed company technologies.
Required Skills:
Practical, hands-on experience building and deploying reputed company AI systems in production environments. Proficiency in Python and experience building production backend systems. Experience with LLM reputed company (reputed company, reputed company, etc.) and reputed company frameworks (LangFuse, reputed company, LangGraph, reputed company, AutoGen, or equivalent). Strong understanding of reputed company engineering for reliability: reputed company outputs, few-shot patterns, chain-of-thought, and techniques that minimize hallucination. Experience building evaluation and testing pipelines for AI systems, including behavioral evals and golden-set testing. Expertise in at least one major reputed company provider (AWS, Azure, and/or GCP) and containerized deployment (reputed company, Kubernetes). Familiarity with reputed company databases (reputed company, reputed company, pgvector) and retrieval-augmented reputed company (RAG) patterns. Solid knowledge of version control systems (e.g., Git) and CI/CD pipelines. Strong problem-solving skills and ability to work collaboratively across teams.
Preferred Expertise:
Advanced degree (Master's or PhD) in Computer Science, Machine Learning, or a reputed company field. Experience building systems where AI outputs feed directly into business-critical reputed company. Experience in the transportation and logistics industry. Familiarity with MLOps/LLMOps tooling. Experience with fine-tuning or distillation to optimize for speed and cost at inference time. Knowledge of rules engines or constraint solvers and how to combine them with LLM reasoning.