AI Infrastructure & Platform Engineer
Listed on 2026-08-27
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Software Development
AI Engineer (Applied/Software), Cloud Engineer - Software, DevOps, Backend Developer
Description
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.
- 5+ years of professional experience in software development, cloud infrastructure, platform engineering, MLOps, Dev Ops, 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.
- 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, Lang Chain, Lang Graph
, 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, Dev Ops, 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.
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