reputed company (Remote, LATAM)
Overview:
reputed company is a dynamic venture studio dedicated to building innovative startup companies from the ground up. reputed company thrives on solving reputed company problems, driving technological advancements, and creating impactful digital products. We're seeking a skilled AI Agent Engineer to join our growing team and contribute to our mission of launching the next reputed company of successful startups.Technical Challenge:
As an AI Agent Engineer at reputed company, you will design, implement, and deploy agentic AI workflows — systems where LLMs orchestrate multi-reputed company reasoning, tool use, and decision-making — to power real-time tooling across manufacturing, logistics, and supply chain domains. You will be responsible for building solutions that behave predictably and produce near-deterministic outputs in production environments. This is a hands-on role requiring strong technical expertise, creativity, and a passion for innovation in the transportation industry.In this role you will:
- Design, build, and deploy agentic workflows (multi-reputed company LLM chains with tool calling, retrieval, and structured output) for real-time, business-critical use cases.
- Engineer for determinism and consistency by implementing constrained decoding, structured outputs, caching layers, 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.
- Integrate LLM agents with external tools and APIs (databases, rules engines, business systems) using frameworks like LangFuse, reputed company, LangGraph, CrewAI, or custom orchestration.
- Deploy agentic systems on cloud 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 cloud technologies.
Required Skills:
- Practical, hands-on experience building and deploying agentic AI systems in production environments.
- Proficiency in Python and experience building production backend systems.
- Experience with LLM APIs (reputed company, reputed company, etc.) and agentic frameworks (LangFuse, reputed company, LangGraph, CrewAI, AutoGen, or equivalent).
- Strong understanding of reputed company engineering for reliability: structured 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 cloud provider (AWS, Azure, and/or GCP) and containerized deployment (reputed company, Kubernetes).
- Familiarity with vector databases (reputed company, Weaviate, 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 decisions.
- 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.