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Work where work matters. We are a global technology group built for what's next, offering high calibre professionals the platform for high stakes work, the kind of work that defines an entire career. When you join us, you're not just taking on projects, you're solving problems that don't even have answers yet. You will join an exclusive roster of talent that global leaders, including Google, Snap, Diageo, PayPal, and Jaguar Land Rover call when deadlines seem impossible, when others have already tried and failed, and when the solution absolutely has to work. Forget routine consultancy. You will operate where technology, design, and human behaviour meet to deliver tangible outcomes, fast. This is work that leaves a mark, work you'll be proud to tell your friends about. We are seeking an AI Engineer with expertise in Vertex AI, Python, and Large Language Models to join our Americas team. In this role, you will be responsible for building and supporting production-grade AI solutions that power next-generation intelligent applications for our enterprise clients in North America. Based in Argentina, you will work as part of a core technical team to deliver high-performance AI systems. You will focus on engineering tasks related to generative AI, RAG architectures, and agentic systems, collaborating with our senior engineers and global teams in Europe to translate requirements into technical reality. We look for people who embody: Innovation to solve complex problems Accountability for every result Integrity always About The Role Build AI Solutions : Develop and deploy AI features, including RAG (Retrieval-Augmented Generation) pipelines, LLM orchestrations, and Agentic workflows under the guidance of senior architects Develop Core Logic : Write clean, maintainable, and highly efficient code in Python to support AI model integration and data-intensive applications Optimize Model Performance : Fine-tune models for specific business logic and optimize LLM prompts to ensure accuracy, relevance, and safety for enterprise use cases Engineer Data Sources : Optimize and manage data sources and vector databases to ensure high-quality retrieval for context-aware AI systems Collaborate Globally : Work closely with US-based product owners and European delivery teams, requiring a proactive communication style and flexibility for early-morning syncs Implement Observability : Apply best practices in AI observability and evaluation frameworks to ensure the reliability and quality of enterprise-level deployments Consult with Clients : Partner with clients to develop new AI concepts and enhancements, translating business goals into technical AI roadmaps This role is designed for impact, and we believe our best work happens when we connect. While we operate a flexible model, we expect you to spend regular quality time on site (at our offices or a client location) for collaboration sessions, customer meetings, and internal workshops. As our hiring team is international, we kindly ask that you submit your CV in English to ensure it can be reviewed by all stakeholders. Requirements What Success Looks Like Engineering Experience: 2+ years of professional experience in software engineering, with a focus on AI/ML implementation and Python development AI/ML Integration : Practical experience with the Vertex AI ecosystem and integrating LLMs into web applications Python Expertise : Mastery of the Python ecosystem, specifically libraries used for AI development and data manipulation GCP Proficiency : Hands-on experience with Google Cloud Platform services, specifically Vertex AI, BigQuery, and Cloud Functions DevOps Skills : Proficiency with Docker and CI/CD pipelines as they apply to MLOps workflows Communication : Fluent English skills with the ability to discuss technical trade-offs clearly with both peers and stakeholders Nice to Have AI Frameworks: Deep experience with LangChain or LlamaIndex Data Engineering: Understanding of data pipelines and ETL processes to support AI model training and retrieval Advanced RAG: Experience with sophisticated retrieval techniques and vector search optimization Certifications: GCP Professional Machine Learning Engineer Benefits We believe in supporting our team members both professionally and personally. Here's how we invest in you: OSDE 210 for family group Work from Home Allowance Birthday leave 10 paid learning days per year Bonusly 100 points per month to recognise colleagues Diversity and Inclusion At Beyond, we champion diversity and inclusion. We believe that a career in IT should be open to everyone, regardless of race, ethnicity, gender, age, sexual orientation, disability, or neurotype. We value the unique talents and perspectives that each individual brings to our team, and we strive to create a fair and accessible hiring process for all.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.