What are the responsibilities and job description for the DevOps Engineer position at Incedo Inc.?
About Incedo:
Incedo is a global AI and data transformation specialist empowering companies to realize sustainable business impact from their digital investments by delivering ROI from AI@Scale. As a long-term partner for strategy to execution, we operate at the intersection of business and technology. Our integrated services and platforms are built on the foundation of AI & Data, digital engineering, and operations transformation, bringing deep domain expertise and full stack capabilities together. With over 4,000 people in the US, Canada, Latin America and India and a large, diverse portfolio of Fortune 500 enterprises and fast-growing clients worldwide, we work across banking & payments, wealth management, telecom, hi-tech and life sciences.
Please visit the linke to know about Incedo: https://www.incedoinc.com/
Job Title: Senior DevOps Engineer (AI Platform)
Location: Fort Mill, SC (Hybrid – 3 Days Onsite)
Job Type: Full-Time (FTE)
Position Overview
We are seeking a highly skilled Senior DevOps Engineer to join our engineering team in Fort Mill, SC. This is a hands-on role requiring deep expertise in AWS, Kubernetes, Terraform, Ansible, CI/CD, Infrastructure as Code (IaC), and cloud automation. The ideal candidate will also have exposure to AI/ML infrastructure and experience supporting Generative AI or Agentic AI applications in production.
You will work closely with Software Engineering, Platform Engineering, AI/ML teams, and Cloud Architects to build scalable, secure, and highly available cloud infrastructure while driving automation and DevOps best practices.
Key Responsibilities
Cloud Infrastructure & Automation
- Design, implement, and maintain highly available cloud infrastructure on AWS.
- Build and manage Infrastructure as Code (IaC) using Terraform.
- Automate infrastructure provisioning, configuration management, and deployments using Ansible.
- Manage cloud networking, IAM, VPCs, Load Balancers, Auto Scaling Groups, Route53, S3, EKS, EC2, RDS, Lambda, CloudWatch, and related AWS services.
- Optimize cloud environments for scalability, reliability, performance, and cost.
Kubernetes & Containerization
- Deploy and manage containerized applications using Docker and Kubernetes (EKS preferred).
- Configure Kubernetes deployments, services, ingress controllers, namespaces, ConfigMaps, Secrets, Helm Charts, and autoscaling.
- Monitor cluster health and troubleshoot production issues.
- Ensure high availability and disaster recovery strategies.
CI/CD & DevOps
- Design and maintain CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
- Automate application deployments across development, QA, staging, and production environments.
- Integrate security scanning, testing, and compliance into deployment pipelines.
- Support blue-green deployments, canary releases, and rolling deployments.
AI/ML Platform Support
- Support infrastructure for Generative AI and Agentic AI applications.
- Deploy AI workloads using Kubernetes and cloud-native services.
- Collaborate with AI/ML engineers to optimize GPU-enabled infrastructure.
- Support AI model deployment, inference services, and scalable AI platforms.
- Work with vector databases, AI APIs, or LLM-based applications (preferred).
Monitoring & Production Support
- Implement monitoring and alerting using Prometheus, Grafana, CloudWatch, Datadog, ELK, or Splunk.
- Troubleshoot production issues and perform root cause analysis.
- Ensure system uptime, reliability, and performance.
- Participate in production support and incident management.
Security & Best Practices
- Implement IAM policies and cloud security best practices.
- Ensure infrastructure complies with organizational security standards.
- Manage secrets, certificates, and secure deployment practices.
- Collaborate with Security and Infrastructure teams on governance and compliance initiatives.
Required Qualifications
- Bachelor's degree in Computer Science, Information Technology, or related field.
- 7 years of DevOps or Cloud Engineering experience.
- Strong hands-on experience with AWS Cloud.
- Extensive experience with Kubernetes (EKS preferred).
- Strong expertise in Terraform for Infrastructure as Code.
- Hands-on experience with Ansible for configuration management and automation.
- Strong experience with Docker and container orchestration.
- Experience building and maintaining CI/CD pipelines.
- Strong Linux administration and troubleshooting skills.
- Experience with Git, branching strategies, and version control.
- Proficiency in scripting using Python and/or Shell (Bash).
- Strong understanding of networking, DNS, SSL/TLS, IAM, security groups, and load balancing.
- Excellent troubleshooting and production support experience.
Preferred Qualifications
- Experience supporting Generative AI, LLM, or Agentic AI workloads.
- Experience deploying AI/ML models into production.
- Exposure to LangChain, OpenAI APIs, Hugging Face, Bedrock, Vertex AI, or Azure OpenAI.
- Experience with GPU-enabled Kubernetes clusters.
- Knowledge of MLOps concepts and AI infrastructure.
- Experience with GitOps tools such as ArgoCD or FluxCD.
- AWS Solutions Architect, AWS DevOps Engineer, CKA, CKAD, or Terraform certifications are a plus.
Required Technical Skills
- AWS (EC2, EKS, S3, IAM, Lambda, CloudWatch, RDS, VPC)
- Kubernetes (EKS)
- Docker
- Terraform
- Ansible
- Jenkins / GitHub Actions / GitLab CI
- Python
- Bash
- Linux
- Git
- Helm
- Prometheus
- Grafana
- Datadog
- ELK
- Cloud Security
- Infrastructure as Code
- CI/CD
- AI Infrastructure
- Generative AI (Preferred)
- Agentic AI (Preferred)
Nice to Have
- Experience with LaunchDarkly
- MLOps experience
- Vector databases (Pinecone, Weaviate, FAISS)
- LangChain
- OpenAI / Azure OpenAI
- Bedrock
- Kafka
- ArgoCD
- FinOps and cloud cost optimization