Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.
Job Description
Job Title:
Senior Staff Software Engineer Location:
Remote/North Chicago Area Duration:
5 months Position Summary We are seeking a highly skilled Senior Staff Software Engineer to design, build, and scale next-generation AI platforms and intelligent systems. The ideal candidate will possess strong software engineering fundamentals, deep expertise in distributed systems, cloud-native infrastructure, machine learning platforms, and operational excellence. This role involves developing production-grade AI applications, shared services, internal platforms, and foundational infrastructure that support large-scale AI workloads across enterprise environments. Key Responsibilities Design, develop, and maintain scalable software systems using C/C++, Python, Go, Rust, Node.js, and other modern programming languages. Build advanced AI solutions including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, agentic AI systems, vector databases, and multi-agent architectures. Research, design, and optimize high-performance AI workloads for CPU, GPU, and heterogeneous computing environments. Develop internal platforms, SDKs, shared services, and infrastructure components that accelerate engineering productivity. Create rapid prototypes and production-ready solutions while maintaining high standards of software quality and maintainability. Design and implement inference serving platforms for deep learning and generative AI applications. Establish engineering best practices for testing, debugging, CI/CD, automated deployments, monitoring, observability, incident management, and operational excellence. Drive architecture reviews, technical strategy, and platform modernization initiatives. Collaborate with data scientists, ML engineers, platform engineers, security teams, and product stakeholders to deliver enterprise-scale AI solutions. Manage Kubernetes-based environments including cluster lifecycle management, version upgrades, service mesh administration, GitOps workflows, and Argo-based deployments. Implement secure authentication and authorization mechanisms using SSO, OAuth2, OIDC, SCIM, and enterprise identity governance frameworks. YOE 5+ years
Additional:
Years of experience/education and/or certifications required: 5 Years min and AWS Certification What are the top 3-5 skills requirements should this person have? Strong software engineering background with systems programming experience in languages like C/C++, Python, Go, Node, and Rust, plus solid fundamentals in data structures, algorithms, and concurrency. Experience in rapid prototyping with Python, along with knowledge of software engineering principles and foundational computer science. Familiarity with AI/ML development, including fine-tuning large language models, multi-agent systems, RAG pipelines, vector databases, and deep learning frameworks like TensorFlow and PyTorch. Understanding of advanced compute and infrastructure topics such as GPUs, heterogeneous accelerators like cuda, modern inference serving, shared services, internal platforms, testing, CI/CD and Kubernetes. Basic knowledge of identity and access management concepts, including SSO, OAuth/OIDC, SCIM, authentication protocols, access lifecycle management, and identity governance. What is a nice to have (but not required) regarding skills, requirements, experience, education, or certification? Master's in computer science, Artificial Intelligence, Machine Learning, Distributed Systems, platform engineering and developer experience (DevEx) or a related field.
