AI Engineer

🔥 3 hours ago

💃 Latin America – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Avenga

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

🏭 Manufacturing

🏥 Healthcare

💰 Private equity on 2017-02

Consulting • Manufacturing • Healthcare

Avenga is an international technology and software engineering company that combines consulting, product development, and digital transformation services to help enterprises solve complex business and societal challenges. With over 6,000 professionals across multiple countries and decades of experience, Avenga delivers custom software, cloud, and integration solutions while supporting clients across industries and providing talent acquisition and career development services internally.

📋 Description

• Design and develop reusable components, libraries, APIs, plugins, and tools that enable AI adoption across products and engineering teams • Integrate AI capabilities into the internal development framework and make them easy for engineering teams to adopt • Define reference architectures, technical patterns, standards, and best practices for Generative AI-based solutions • Design and implement integrations with Large Language Models and AI services, primarily within the AWS ecosystem • Develop production-ready solutions using Node.js, TypeScript, serverless architectures, and the Serverless Framework • Explore and implement structured generation, tool calling, agents, RAG, MCP, embeddings, and semantic search • Define testing and evaluation mechanisms for quality, security, latency, reliability, and cost of AI-powered solutions • Implement observability for model usage, prompts, tokens, responses, errors, execution times, and other operational metrics • Establish technical controls and engineering practices for secure and responsible AI usage • Build proof-of-concepts and evolve successful approaches into scalable, maintainable, production-ready solutions • Create technical documentation, implementation examples, and adoption guidelines • Support development teams in adopting reusable AI components, architectures, and engineering best practices • Participate in architecture reviews and contribute to technical decision-making • Share knowledge and promote AI engineering best practices

🎯 Requirements

• Senior-level experience in backend software development • Strong expertise in Node.js and solid experience with JavaScript and/or TypeScript • Hands-on experience with AWS, serverless architectures, and distributed systems • Experience designing and developing APIs, libraries, frameworks, plugins, or other reusable software components • Strong understanding of software design principles and engineering best practices, including testing, security, observability, and CI/CD • Experience contributing to software architecture, technical design, and engineering decision-making • Hands-on experience developing or integrating solutions based on Large Language Models (LLMs) and Generative AI • Ability to translate business and technical requirements into generic, scalable, and reusable solutions • Ability to research emerging technologies, evaluate alternatives, and transform concepts and proof-of-concepts into production-ready solutions • Self-driven mindset with a high degree of ownership and autonomy • Strong communication, technical documentation, and cross-team collaboration skills • Experience with Amazon Bedrock or other Generative AI platforms • Experience with the Serverless Framework and plugin development • Hands-on knowledge of RAG, AI agents, tool calling, Model Context Protocol (MCP), structured generation, embeddings, and semantic search • Experience with AWS services such as Lambda, API Gateway, Step Functions, EventBridge, SQS, SNS, and DynamoDB • Knowledge of vector databases and semantic search technologies • Experience implementing evaluation frameworks, guardrails, observability, and operational practices for LLM-based applications • Experience building internal development platforms, frameworks, or developer tools

🏖️ Benefits

• Equal opportunities in recruitment, career development, and leadership • Diverse and inclusive work environment