IMI is seeking an
AI Infrastructure & Platform Engineer to help build and expand our internal AI capabilities.
This is a hands-on opportunity to work across
AI, software development, cloud infrastructure, and systems integration as we develop a scalable and secure foundation for AI across the organization.
Working alongside internal teams and external technology partners, this individual will help design and build our internal AI platform, develop AI-powered workflows and integrations, and bring more AI capabilities in-house over time. The role will also help evaluate when to build solutions internally, when to leverage third-party technologies, and how to securely and reliably bring those solutions into production.
The ideal candidate combines a strong software and cloud infrastructure foundation with hands-on experience with
large language models (LLMs), generative AI, and modern AI application architectures. This person will also serve as an internal advocate for AI adoption, helping technical and non-technical users understand and effectively utilize new AI-powered tools.
Requirements
- 5+ years of professional experience in software development, cloud infrastructure, platform engineering, MLOps, DevOps, or a related technical field.
- Strong software development fundamentals with experience building, deploying, and supporting production applications or services.
- Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
- Experience with modern software deployment practices, including CI/CD and development, staging, and production environments.
- Experience developing and maintaining APIs and integrations between applications, cloud platforms, data sources, and third-party services.
- Hands-on familiarity with modern AI technologies, LLMs, generative AI, and production AI/ML systems.
- Understanding of application, infrastructure, and data security best practices.
- Strong written and verbal English communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
- Resourceful, collaborative, and comfortable working independently in an evolving technical environment.
- Ability to champion new technologies and work effectively across the organization to support AI adoption.
Preferred Qualifications
- Experience with AI agents, RAG, vector databases, AI orchestration frameworks, or LLM-powered workflows.
- Experience with cloud-native and infrastructure technologies such as Docker, Kubernetes, Terraform, or similar tools.
- Familiarity with Model Context Protocol (MCP) or similar AI integration standards.
- Experience with technologies such as Anthropic Claude, OpenAI, Google Gemini, Hugging Face, LangChain, LangGraph, or comparable AI platforms and frameworks.
- Experience customizing, fine-tuning, or deploying private or domain-specific language models.
- Experience working with sensitive financial, trading, or other regulated data.
- Familiarity with SOC 2 or similar security, compliance, and data governance frameworks.
- Full-stack development experience is a plus.
- Relevant cloud or AI certifications are a plus.
- 5+ years of professional experience in software development, cloud infrastructure, platform engineering, MLOps, DevOps, or a related technical field.
- Strong software development fundamentals with experience building, deploying, and supporting production applications or services.
- Hands-on experience with at least one major cloud platform such as AWS, Azure, or GCP.
- Experience with modern software deployment practices, including CI/CD and development, staging, and production environments.
- Experience developing and maintaining APIs and integrations between applications, cloud platforms, data sources, and third-party services.
- Hands-on familiarity with modern AI technologies, LLMs, generative AI, and production AI/ML systems.
- Understanding of application, infrastructure, and data security best practices.
- Strong written and verbal English communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
- Resourceful, collaborative, and comfortable working independently in an evolving technical environment.
- Ability to champion new technologies and work effectively across the organization to support AI adoption.
