AI Engineer

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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
 

BRG’s AI Department is seeking an AI Infrastructure Engineer (Mid‑Level) to support the next phase of our Virtual AI Lab initiative. After completing Phase 01—the build-out of our physical AI Lab—this role will help design, implement, and scale the virtual access layer that enables teams across BRG to remotely use our high‑performance AI infrastructure. You will work on systems capable of processing 100,000+ documents per day using advanced LLMs from OpenAI and Anthropic.

This role is ideal for an engineer with solid cloud, infrastructure, and AI/ML engineering experience who is ready to take ownership of meaningful components, contribute to architectural decisions, and help build a cutting‑edge capability from the ground up.

We are expanding our team in Argentina, offering a rare opportunity to shape a new engineering function within a global AI organization.

Key Responsibilities

• Contribute to the design and implementation of the Virtual AI Lab access layer
• Build scalable remote compute capabilities supporting 100,000+ documents/day
• Develop customizable and expandable virtual interfaces for BRG business units
• Implement and maintain secure authentication and access‑management systems

• Optimize infrastructure for high LLM token throughput (OpenAI / Anthropic)
• Support high‑availability architectures and fault‑tolerant systems
• Participate in performance tuning, load testing, and resource optimization

• Collaborate on infrastructure projects from design to production deployment
• Build and maintain cloud/hybrid environments using IaC tools
• Support API integrations, distributed systems components, and workflow automation
• Contribute to monitoring, metrics, and reliability engineering practices

Required Qualifications

Ideal candidates have experience building production systems, contributing to platform reliability, and collaborating with domain experts in high‑stakes environments.

Minimum Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field
• 3–6 years of hands-on experience designing, deploying, or supporting cloud infrastructure
• Experience with Infrastructure as Code (Terraform, CDK, CloudFormation)
• Exposure to LLM applications (extraction, summarization, classification, RAG, tool use)
• Familiarity with evaluation frameworks: prompt testing, offline/online evaluation, monitoring, error analysis
• Experience with data/workflow engineering, including pipelines, transformations, and metadata
• Applied ML or NLP exposure (classical ML, anomaly detection, entity resolution, forecasting)
• Understanding of security and governance principles: privacy-by-design, access controls, safe data handling
• Experience maintaining scalable, secure, cost‑efficient cloud or hybrid environments
• Proficiency in version control (Git/GitHub), Python, and modern development practices (SDLC, CI/CD)
• Experience building or integrating APIs for distributed systems
• Familiarity with GPU infrastructure or compute optimization for AI workloads
• Hands-on experience with AWS services such as:
  • EC2 / Lambda
  • S3
  • SageMaker
  • Fargate / ECS / EKS
  • Terraform / CDK
  • Cost monitoring tools (Cost Explorer/Budgets)

Preferred Qualifications

• Experience deploying or optimizing LLMs (OpenAI, Anthropic, etc.)
• Background supporting or building AI/ML platforms or pipelines
• Experience with VDI or remote-access technologies
• Familiarity with distributed computing frameworks or job‑scheduling systems
• AWS certifications (Solutions Architect, SysOps, Developer, ML Specialty)
• Experience with cloud cost‑efficiency strategies
• Exposure to one or more of the following domains:
  • Healthcare (provider systems, workflows, RCM)
  • Litigation / eDiscovery / Investigations
  • Corporate Finance / Restructuring / Disputes
  • IP / Tech / ISP (data-intensive technical work)

Why Join Us

• Work on a groundbreaking Virtual AI Lab powering mission‑critical workloads
• Influence foundational infrastructure decisions and engineering standards
• Collaborate with senior engineers working on cutting‑edge AI systems
• Career growth opportunities as the Argentina team continues to scale
• High-impact, real-world problem-solving in a fast-evolving AI landscape

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.