AI Lab Junior Engineer

We do Consulting Differently

BRG’s Ai Department is seeking an AI Infrastructure Senior Engineer to lead the development of our Virtual Ai Lab initiative. Following the successful completion of Phase 01 (physical Ai Lab build-out), this role will focus on creating a virtual access layer that makes our high-performance Ai Lab remotely accessible to teams across BRG. The ideal candidate will design and implement scalable infrastructure to support processing 100,000+ documents daily using state-of-the-art LLMs from OpenAI and Anthropic.

About The Role

As a Junior AI Infrastructure Engineer, you will support the development of the virtual access environment for our physical AI Lab, helping enable secure, scalable, and high‑performance remote processing for teams across BRG. You’ll work closely with senior engineers to build the systems that allow users to access and leverage the Lab’s computational power from anywhere, supporting large‑scale document processing and advanced LLM workloads.

In this role, you will assist in creating and configuring virtual interfaces for different BRG groups, contribute to implementing secure access controls, and help monitor resource usage and performance across concurrent users. Your work will play an important part in ensuring a smooth, reliable, and efficient experience for teams interacting with our AI Lab.

We are building our team in Argentina, and this is a unique opportunity to join a cutting‑edge capability from the ground up. You’ll gain hands‑on experience, learn from senior engineers, and contribute to high‑impact infrastructure that supports some of BRG’s most demanding workloads.

Key Responsibilities

Ideal candidates are passionate about building real AI solutions—not just prototypes—and are eager to contribute to production‑grade systems. They should be comfortable collaborating with senior engineers and domain experts, learning rapidly, and working in environments where accuracy, security, and reliability matter.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field
• 2-4 years of hands‑on experience through internships, academic projects, research, or early professional roles
• Foundational understanding of cloud infrastructure (AWS, Azure, or GCP)—professional, academic, or project-based
• Basic familiarity with Infrastructure as Code concepts (Terraform, CDK, or similar)
• Exposure to LLM applications, such as summarization, extraction, classification, or simple RAG workflows
• Interest or experience in evaluation and quality techniques for LLMs (prompt testing, monitoring basics, error analysis)
• Working knowledge of Python and modern software development practices (Git/GitHub, code reviews, testing)
• Exposure to data engineering fundamentals: pipelines, transformations, metadata, workflow automation
• Academic or practical exposure to applied ML, such as classical ML, NLP tasks, or forecasting
• Awareness of security best practices, including responsible data handling and access control basics
• Experience designing or supporting small‑scale systems or applications (university, personal projects, internships)
• Familiarity with APIs and integrating them into applications or workflows
• Exposure to GPU environments (university labs, Kaggle, cloud credits, or project work)

Experience with AWS services is a plus but not required; familiarity with any of the following is valuable:

• EC2 or Lambda (running workloads)
• SageMaker (training/experimenting)
• S3 (storage)
• ECS/EKS/Fargate (container basics)
• CDK/Terraform (infrastructure basics)
• Cost monitoring awareness (cost visibility or tagging)

Preferred Qualifications

• Hands‑on project or internship work involving LLMs (OpenAI, Anthropic, etc.)
• Experience contributing to or helping build AI/ML pipelines or infrastructure
• Exposure to virtual desktop infrastructure (VDI) or remote‑access systems
• Familiarity with distributed systems concepts or job scheduling tools
• AWS academic coursework, cloud practitioner certifications, or cloud fundamentals
• Experience participating in team‑based software projects (internships, hackathons, open‑source contributions)
• Awareness of cost‑efficient design principles in cloud environments
• Interest in or familiarity with one or more of these domains:
  • Healthcare analytics
  • Litigation / eDiscovery / Investigations
  • Corporate Finance / Restructuring / Disputes
  • IP / Technology / Data‑intensive expert work

About BRG
 
BRG combines world-leading academic credentials with world-tested business expertise purpose-built for agility and connectivity, which sets us apart—and gets you ahead.

At BRG, our top-tier professionals include specialist consultants, industry experts, renowned academics, and leading-edge data scientists. Together, they bring a diversity of proven real-world experience to economics, disputes, and investigations; corporate finance; and performance improvement services that address the most complex challenges for organizations across the globe.

Our unique structure nurtures the interdisciplinary relationships that give us the edge, laying the groundwork for more informed insights and more original, incisive thinking from diverse perspectives that, when paired with our global reach and resources, make us uniquely capable to address our clients’ challenges. We get results because we know how to apply our thinking to your world.

At BRG, we don’t just show you what’s possible. We’re built to help you make it happen.  

BRG is proud to be an Equal Opportunity Employer. Our hiring practices provide equal opportunity for employment without regard to race, religion, color, sex, gender, national origin, age, United States military veteran status, ancestry, sexual orientation, marital status, family structure, medical condition including genetic characteristics or information, veteran status, or mental or physical disability so long as the essential functions of the job can be performed with or without reasonable accommodation, or any other protected category under federal, state, or local law.