Company Description
Wekalp is a Data Intelligence and Automation Platform that enables AI agents to act on reliable, governed enterprise data. Our living semantic layer captures the context of how businesses actually run — and surfaces it as conversational intelligence, automated pipelines, and board-ready insights. We currently serve BFSI and CPG enterprises, are CERT-IN certified and provide flexible deployment options across customer, shared, or on-premise cloud.
Key responsibilities
- Administer Red Hat OpenShift / Kubernetes (OKD) clusters — installation, upgrades, operators, ingress, RBAC, networking, and security policies.
- Design and manage AWS infrastructure (EKS, EC2, S3, RDS, Route 53) including IAM, VPC, and security groups. Wekalp's data and storage layer is platform-native — this role manages the infrastructure it runs on, not AWS data services
- Build and maintain CI/CD pipelines (Jenkins, GitLab CI, or GitHub Actions) for containerized microservice and platform deployments.
- Deploy and operate Wekalp's platform in customer-managed environments — on-premise data centres and customer clouds (AWS, Azure, or GCP tenants) — including air-gapped setups, private networking constraints, and customer-specific security policies.
- Own cross-environment interoperability: ensure consistent platform behaviour, configuration parity, and upgrade paths across Wekalp-hosted and customer-hosted deployments.
- Manage AWS Bedrock service integration — API availability, request routing, IAM permission boundaries, and cost monitoring for inference workloads.
- Support deployment and connectivity of MCP servers that we build for enterprise customers integrating with Claude — including networking, auth, and endpoint reliability.
- Ensure observability across platform services: Prometheus, Grafana dashboards covering infra health, API latency, and Bedrock usage metric
Qualifications
- 2–4 years of hands-on DevOps or platform engineering experience.
- Proficient with Red Hat OpenShift or Kubernetes cluster administration.
- AWS infrastructure experience: EKS, EC2, Route 53, IAM, and VPC. Note: Wekalp's data and storage layer is platform-native — familiarity with AWS compute and networking is what's needed, not AWS data services
- Experience deploying software into customer-managed environments — on-premise or private cloud — including handling restricted networks, custom TLS, and enterprise proxy configurations
- CI/CD pipeline design using Jenkins, GitLab CI, or GitHub Actions. Docker and container image lifecycle management.
- Linux administration, cloud networking, and security fundamentals.
- Familiarity with Prometheus + Grafana and ELK/EFK logging stacks.
- Automation using Ansible or scripting (Bash/Python)
- Working knowledge of AWS Bedrock — how it's invoked, how access is controlled, and how costs are tracked across foundation model API calls.
- Awareness of MCP (Model Context Protocol) — what it does, how servers expose data to AI agents, and how to keep those connections reliable and secure in an enterprise context.
- Cost-conscious mindset — especially for variable inference workloads on managed AI services.
- Strong troubleshooting instincts and ability to collaborate across data, AI, and product teams
