Position: Cloud Software Engineer - GenAI & MLOps (GCP) We are seeking a skilled
Cloud Software Engineer to join a high-performing cross-functional team responsible for building scalable MLOps platforms and Generative AI (GenAI) solutions. You will collaborate with data scientists, software engineers, product managers, and business partners to accelerate the delivery of innovative AI/ML capabilities using
Google Cloud Platform (GCP).
Key Responsibilities: - Design, develop, and maintain MLOps platforms and GenAI solutions in GCP using Python and other modern tools.
- Build reusable AI/ML components and support development of LLM, RAG, and Multi-Agent applications.
- Collaborate with software engineers and data scientists to solve complex AIOps and MLOps challenges.
- Manage and improve the existing CI/CD pipeline and DevOps processes using tools like Jenkins or Tekton.
- utomate infrastructure and workflow using Infrastructure as Code (IaC) tools like Terraform.
- Contribute to code reviews, debugging, and resolving issues in scripts, pipelines, or services.
- Promote best practices in software craftsmanship, including Test-Driven Development (TDD) and Paired Programming.
- Stay current with evolving ML/GenAI, GCP, and Kubernetes ecosystems.
Must-Have Skills & Experience: - Bachelor's degree in Computer Science, Computer Engineering, or a related field.
- 3+ years of experience as a backend software engineer with strong expertise in Python.
- 2+ years of hands-on experience with Cloud services (preferably GCP).
- Proficient in MLOps, GenAI, and LLMs, with practical experience building RAG and multi-agent systems.
- Hands-on experience with ML workflow orchestration tools such as Airflow or Kubeflow.
- Strong understanding of object-oriented programming (OOP) and languages like Python, C/C .
- Experience in DevOps practices and tools (e.g., Jenkins, Tekton).
- Working knowledge of GCP services like Vertex AI, BigQuery, Cloud Functions, etc.
- Familiarity with Kubernetes, Docker, and scripting languages (e.g., Bash, PowerShell).
- Experience using Terraform or similar tools for infrastructure automation.
Preferred Qualifications: - Master's degree in Computer Science, Machine Learning, or a related field.
- Deep knowledge of GCP architecture, Google Kubernetes Engine (GKE), and Terraform.
- Exposure to agile methodologies, including TDD, paired programming, and continuous delivery.
- Proven ability to quickly learn new technologies and apply them in a collaborative, fast-paced environment.
- Excellent communication and teamwork skills.
Other Details: - Work Mode: Hybrid (minimum 2 days/week onsite; subject to change)
- Location: DEARBORN, MI
- Position Type: Full-Time
- Industry: Cloud / AI / ML / DevOps / Software Engineering