Senior Software Engineer AI Job – Red Hat Hiring Remote | High Salary up to $220K
Senior Software Engineer Hiring – AI & MLOps | Red Hat Remote Job
Posted by JobsForAll
Company Overview
Red Hat is a global leader in enterprise open-source software solutions, known for its innovations in Linux, cloud computing, Kubernetes, and automation technologies. The company empowers businesses worldwide by delivering scalable, secure, and high-performance infrastructure solutions.
With operations in over 40 countries, Red Hat fosters a collaborative and inclusive engineering culture, making it one of the most sought-after employers for software engineers and AI professionals.
Job Summary
Red Hat is hiring a Senior Software Engineer – AI Eval and Safety to build next-generation infrastructure for trustworthy AI systems. This role focuses on developing scalable MLOps and LLMOps platforms that ensure AI models are reliable, safe, and aligned with human values.
You will work on cutting-edge technologies including Kubernetes, OpenShift AI, and open-source projects like Kubeflow and KServe, contributing to AI systems used globally across enterprise environments.
💭 JobsForAll Note: AI + MLOps roles are among the highest-paying tech careers today. If you have Kubernetes and AI experience, this is a golden opportunity to enter the global AI infrastructure space.
Eligibility Criteria
- 5+ years of software engineering experience
- 4+ years working with AI/ML systems
- Strong expertise in Python
- Hands-on experience with Kubernetes and MLOps tools
Job Details
| Role | Senior Software Engineer – AI Eval & Safety |
|---|---|
| Company | Red Hat |
| Location | Remote (Boston-based team) |
| Experience | 5+ Years |
| Salary | $133,650 – $220,680 (High Paying) |
| Work Mode | Remote |
Key Responsibilities
- Design and build scalable MLOps and LLMOps systems
- Develop AI safety frameworks including bias detection and monitoring
- Work on Kubernetes-based AI infrastructure
- Contribute to open-source projects like Kubeflow and KServe
- Lead architecture decisions and mentor engineers
- Ensure reliability, scalability, and performance of AI systems
Required Skills
- Python programming
- Kubernetes & container orchestration
- MLOps tools (Kubeflow, MLflow, KServe)
- Distributed systems architecture
- CI/CD and monitoring systems
Who Should Apply for this Post
- Software engineers with experience in AI/ML systems and MLOps
- Professionals skilled in Kubernetes, Python, and distributed systems
- Developers interested in AI safety, LLMOps, and scalable AI platforms
- Engineers looking for high-paying remote opportunities in global companies
Who Should NOT Apply for this Post
- Freshers or candidates without relevant experience in AI/ML
- Applicants without hands-on experience in Kubernetes or backend systems
- Those not comfortable working in advanced, large-scale distributed environments
- Candidates looking only for entry-level or non-technical roles
Compensation Note
This is a high-paying international role with a salary range of $133,650 – $220,680 per year. The final compensation depends on experience, technical expertise, and location. Additional benefits may include bonuses, stock options, and health coverage.
Why This Job is High in Demand 🔥
AI infrastructure and MLOps roles are rapidly growing as companies scale AI systems globally. Engineers who understand both software systems and machine learning pipelines are in extremely high demand in 2026 and beyond.
Career Growth Opportunities
- AI Architect
- Principal Engineer
- ML Platform Lead
- Director of AI Engineering
Application Process
🔥 Apply Quickly (Recommended) Apply through official Red Hat carrer portal NowFrequently Asked Questions (FAQs)
Is this job remote?
Yes, this is a fully remote role.
What is the salary?
The salary ranges from $133K to $220K depending on experience.
Is Kubernetes mandatory?
Yes, strong Kubernetes experience is essential for this role.
References & Resources
- Explore AI Career roadmap before applying
- Explore AI/ML Career roadmap
- ATS Resume Guide
- Avoid Job Scams
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