Forward Deployed Engineer – AI

This is a fully remote position, open to applicants in Uruguay.

📋 Description

• Create and develop resilient ETL/ELT pipelines and data infrastructure for AI-driven applications, guaranteeing high quality and data availability.

• Implement comprehensive data pipelines for Retrieval-Augmented Generation (RAG), encompassing data ingestion, chunking, embedding generation, vector store management, and retrieval optimization.

• Develop evaluation suites and guardrails to assess quality, safety, cost, and latency pre- and post-deployment.

• Integrate AI components into current client systems through REST/GraphQL APIs, event streams, and cloud-native services on AWS, Azure, or GCP.

• Build production-ready applications leveraging LLMs (Claude, GPT, open-source models), which include chat interfaces, copilots, agents, and back-office automation.

• Create agentic workflows utilizing frameworks like the Claude Agent SDK, LangGraph, or similar tools, which involve tool use, planning, and multi-step orchestration.

• Conduct rapid prototyping sprints with clients, delivering a demo-ready product within days and iterating towards production readiness.

• Document architectures, share insights with the broader NextLink AI practice, and contribute to internal accelerators and reference implementations.

⛳️ Requirements

• 3–5 years of professional software engineering experience, including at least 1 year of delivering AI/ML or LLM-based features to production.

• Proficient in Python; familiarity with at least one of TypeScript/JavaScript, Go, or Java for integration tasks.

• Practical experience in developing applications using modern LLM APIs (Anthropic, OpenAI, Azure OpenAI, AWS Bedrock, etc.).

• Background in data engineering tools such as dbt, Airflow, Dagster, Snowflake, BigQuery, or Databricks.

• Working knowledge of RAG patterns, embedding models, and at least one vector store (pgvector, Pinecone, Weaviate, OpenSearch, etc.).

• Strong understanding of a major cloud platform (AWS, Azure, or GCP), including deployment of containerized services and management of secrets/IAM.

• Experience in writing tests, instrumenting code, and considering observability, even in non-deterministic systems.

• Excellent written and verbal English communication skills; comfortable presenting technical work to both client engineering teams and non-technical stakeholders.

• Customer-oriented mindset: you ask insightful questions, handle ambiguity effectively, and remain engaged when challenges arise.

🏝️ Benefits

• Commitment to your development, featuring access to LLM playgrounds, an internal AI guild, and senior architects for guidance.

• The chance to create something significant and thrilling at the forefront of applied AI.

• Remote-first work environment with a strong emphasis on written communication culture (documentation, asynchronous updates, clear pull requests).