Senior Platform Engineer (Python)
Bengaluru, IndiaFull-timeSenior · 6+ years
About this role
About Saarthee:
Saarthee is a Global Strategy, Analytics, Technology and AI consulting company, where our passion for helping others fuels our approach and our products and solutions. We are a onestop shop for all things data and analytics. Unlike other analytics consulting firms that are technology or platform specific, Saarthee’s holistic and tool agnostic approach is unique in the marketplace. Our Consulting Value Chain framework meets our customers where they are in their data journey. Our diverse and global team work with one objective in mind: Our Customers’ Success. At Saarthee, we are passionate about guiding organizations towards insights fueled success. That’s why we call ourselves Saarthee–inspired by the Sanskrit word ‘Saarthi’, which means charioteer, trusted guide, or companion. Cofounded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA with office in UK and India
Position Summary:
We are looking for a highly skilled Platform Engineer with strong expertise in Python, Kubernetes, AWS, and Infrastructure Automation to build and scale cloud-native platform services that power engineering productivity and operational excellence. The ideal candidate will work at the intersection of Platform Engineering, Cloud Infrastructure, SRE, and Developer Experience, driving automation, reliability, observability, and self-service capabilities across the engineering ecosystem.
This role requires hands-on experience with distributed systems, Infrastructure as Code, CI/CD, and cloud native technologies, along with a strong ownership mindset and passion for engineering excellence.
Your Role Responsibilities and Duties:
- Design, build, and maintain scalable platform services and internal developer tools using Python
- Develop automation frameworks, orchestration systems, and backend platform services to improve engineering efficiency
- Build and operate highly available, resilient, and scalable systems in Kubernetes-based environments
- Drive platform reliability, observability, deployment automation, and operational excellence initiatives
- Develop infrastructure automation solutions and Infrastructure-as-Code implementations using Terraform
- Build and maintain cloud-native platforms and services on AWS
- Manage and optimize Kubernetes clusters, containerized workloads, and deployment pipelines
- Deploy and manage applications using Helm, ArgoCD, and Argo Rollouts
- Develop Python-based automation and tooling for operational workflows, reliability engineering, and observability
- Build internal monitoring, alerting, logging, and tracing solutions to improve platform visibility
- Integrate CI/CD pipelines with reliability, observability, and operational governance practices
- Improve developer experience through self-service platforms, automation, and standardized engineering workflows
- Contribute to architecture decisions for distributed systems and cloud-native applications
- Lead incident response activities, root cause analysis, postmortems, and reliability improvement initiatives
- Partner with Product Engineering, SRE, Security, and Architecture teams to improve platform scalability and operational maturity
- Establish best practices for monitoring, testing, deployment automation, security, and production operations
- Create technical documentation, platform standards, and operational runbooks
- Mentor engineers and promote engineering excellence across teams
Required Skills and Qualifications:
- Bachelor's degree in Engineering, Computer Science, or a related field
- 6+ years of experience in Platform Engineering, Site Reliability Engineering (SRE), or DevOps Engineering
- Strong programming expertise in Python with experience building production-grade automation and platform tooling
- Hands-on experience designing and operating Kubernetes-based environments
- Strong experience with AWS cloud services and cloud-native architectures
- Expertise in Infrastructure as Code using Terraform
- Experience with Helm, ArgoCD, and Argo Rollouts
- Hands-on experience with Docker and containerized application deployments
- Experience with automation tools such as Ansible and Packer
- Strong understanding of CI/CD pipelines using GitHub Actions, Jenkins, or similar tools
- Experience with observability and monitoring platforms such as Prometheus, Grafana, Datadog, or Splunk
- Strong knowledge of Linux systems, networking fundamentals, and troubleshooting methodologies
- Understanding of distributed systems architecture and reliability engineering principles
- Familiarity with Software Development Lifecycle (SDLC) and modern engineering practices
- Excellent problem-solving, debugging, and analytical skills
Preferred skills:
- Experience building internal developer platforms and platform engineering solutions
- Experience developing observability, reliability, and operational tooling using Python
- Multi-cluster or multi-region Kubernetes deployment experience
- Experience with Service Mesh technologies such as Istio
- Experience with API Gateway solutions such as Kong
- Knowledge of SLOs, SLIs, Error Budgets, and Reliability Engineering best practices
- Experience with cloud cost optimization and performance tuning
- Exposure to large-scale distributed systems and cloud-native architectures
- Strong mentoring and technical leadership capabilities