Job Title: MLOPS Engineer
Location: Charlotte, NC | Richardson, TX | Phoenix, AZ |Iselin, NJ Onsite role
Duration: 12 Months
Type: Contract W2
Experience: 8+ years
Work mode: 5 days onsite / week
Job Description:
Please share suitable MLOPS Engineer profiles who are comfortable with the above locations and rate. Candidates with strong experience in MLOps, CI/CD pipelines, cloud platforms, model deployment, monitoring, and automation are preferred.
In This Role, You Will
- Lead complex infrastructure initiatives supporting Generative AI and Predictive AI platforms from design to production operations.
- Serve as a technical lead for platforms supporting AI/ML model training, inference, and batch workloads.
- Design, build, deploy, and operate OpenShift-based container platforms optimized for high-performance GPU workloads.
- Build, support and operate scalable GPU SuperPod architecture with large multi-node GPU clusters.
- Own monitoring, ing, and observability using Grafana, Splunk, and enterprise telemetry tools.
- Define SLIs/SLOs and build actionable s to proactively detect performance, capacity, and resiliency risks.
- Build AI- and agent-based automation tools for self-healing, scaling, diagnostics, and incident remediation.
- Apply AIOps techniques to reduce fatigue and improve platform reliability.
- Lead production incident analysis and ensure operational rigor and root-cause prevention.
- Mentor engineers and influence stakeholders across a geographically distributed organization.
Required Qualifications
- 5+ years of infrastructure engineering experience.
- 5+ years troubleshooting complex end-to-end architectures (including CI/CD pipeline).
- 5+ years Linux systems experience.
- 4+ years supporting AI/ML platforms.
- 4+ years of Kubernetes / container platform experience including production support.
Desired Qualifications
- Experience with Generative AI and Predictive AI platforms.
- Hands-on GPU platform operations including scheduling, quota, and performance tuning.
- Experience with OpenShift in GPU-enabled, multi-tenant environments.
- Experience designing or operating GPU Super Pods.
- Deep experience with observability using Grafana, Splunk, and custom telemetry pipelines.
- Experience building AI- or agent-driven automation tooling (AIOps).
- Hands-on experience supporting AI/ML workloads on GCP and Azure, including GPU-backed services and managed AI infrastructure
- Experience operating hybrid or multi-cloud AI platforms, with an understanding of cloud-native services, networking, identity, and cost optimization for Generative and Predictive AI
- Strong monitoring of AI signals such as inference latency and GPU utilization.
- Experience with BCP/DR, resiliency, and highly available architectures.
Job Expectations
- Participation in a 24x7 on-call rotation.
- Ownership for production stability, platform health, and customer outcomes.
- Operate in regulated enterprise environments with strong risk and control focus.
About Next Gen Software Solutions:
Next Gen Software Solutions is a trusted provider of IT Staffing and consulting services dedicated to empowering businesses with cutting-edge technology solutions and exceptional talent. We specialize in delivering tailored IT consulting services, innovative software solutions, and connecting businesses with highly skilled IT professionals. Founded and led by a dedicated U.S. Army solider, Next Gen Software Solutions is deeply rooted in the core values of integrity, discipline, commitment, and experience-principles that guide every aspect of our operations.
Equal Employment Opportunity Statement:
Next Gen Software Solutions is an Equal Opportunity Employer. We are committed to fostering an inclusive and diverse workplace where all employees and applicants are treated respect and dignity. We do not discriminate based on race, colour, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, genetic information, veteran status, or any other legally protected characteristic under applicable federal, state, or local laws.