Enterprise Platform Architect DevOps

Ericsson; Dadri; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Ericsson is seeking an Architect - AI and DevOps to define secure, scalable AI solutions for enterprise environments. You will shape architectural standards and guide adoption of Generative AI, LLMs, intelligent agents, and automation across platforms.

Collaborate with engineering, product, security and platform teams to translate strategic goals into reliable, production-ready designs. You will lead end-to-end architecture, promote responsible AI practices, and uphold governance and cost

Qualifications

• Experience designing and implementing enterprise AI, ML, cloud or DevOps solutions.
• Strong understanding of AI/ML architecture, deep learning, large language models and modern AI applications.
• Proficiency in Python and practical experience with PyTorch or TensorFlow.
• Experience with prompt engineering, Retrieval-Augmented Generation, embeddings, vector databases, model integration and performance optimization.
• Knowledge of AI agent frameworks, workflow orchestration, tool calling, API integration and the Model Context Protocol.
• Hands-on experience with Git, Ansible, CI/CD design, Python or Bash scripting, JSON and YAML. GitLab experience is an advantage.
• Familiarity with code quality and security tools, artifact repositories and container registries.
• Experience with AWS, Azure or Google Cloud, Docker, Kubernetes, microservices, networking and identity management.
• Knowledge of Ubuntu and Red Hat Enterprise Linux environments, monitoring, logging, observability and production support.
• Strong communication, collaboration and problem-solving skills, with the ability to work across technical and business teams.

Responsibilities

• Define end-to-end AI and ML architectures that meet requirements for performance, availability, security, scalability and cost.
• Design enterprise solutions using large language models, prompt engineering, model tuning, efficient model deployment and secure integration.
• Consulting & Business Generation: Work with Customer Units to propose Automation and AI Solutions & capabilities in the Telecom Service Domain. Contribute to creation of End to end solution, presales estimates and work on Statement of Work and compliance document.
• Architect knowledge solutions using Retrieval-Augmented Generation, embeddings, vector databases and semantic search.
• Design intelligent agents, tool integrations and workflow orchestration using APIs and the Model Context Protocol.
• Establish standards for automated delivery pipelines covering source control, testing, security checks, artifact management, deployment and validation.
• Design cloud-native solutions using AWS, Azure or Google Cloud, Docker, Kubernetes and microservices.
• Guide infrastructure automation, configuration management and Infrastructure as Code using Ansible and related tools.
• Embed privacy, access control, security, compliance and responsible AI practices, including human approval where appropriate.
• Promote effective monitoring, logging, performance improvement and production troubleshooting.
• Communicate architectural decisions clearly and support teams in delivering consistent, high-quality solutions.

Skills

Enterprise AI

ML architecture

Python

PyTorch/TensorFlow

Prompt engineering

Model Context Protocol

CI/CD

Git

Docker

Kubernetes

Cloud platforms

Security & compliance

Linux

Tools

Git

Ansible

CI/CD tooling

Docker

Kubernetes

GitLab

JSON/YAML

Job description

Join our Team

About this opportunity

Join our team as an Architect - AI and DevOps, helping define and deliver secure, scalable and cost-effective AI solutions for enterprise environments. You will shape architectural standards and guide the adoption of Generative AI, large language models, intelligent agents and automation across technology platforms and delivery processes.

Working with engineering, product, security and platform teams, you will connect strategic goals with practical solutions that are reliable, maintainable and ready for production.

What you will do

• Define end-to-end AI and machine learning architectures that meet requirements for performance, availability, security, scalability and cost.
• Design enterprise solutions using large language models, prompt engineering, model tuning, efficient model deployment and secure integration.
• Consulting & Business Generation: Work with Customer Units to propose Automation and AI Solutions & capabilities in the Telecom Service Domain. Contribute to creation of End to end solution, presales estimates and work on Statement of Work and compliance document.
• Architect knowledge solutions using Retrieval-Augmented Generation, embeddings, vector databases and semantic search.
• Design intelligent agents, tool integrations and workflow orchestration using APIs and the Model Context Protocol.
• Establish standards for automated delivery pipelines covering source control, testing, security checks, artifact management, deployment and validation.
• Design cloud-native solutions using AWS, Azure or Google Cloud, Docker, Kubernetes and microservices.
• Guide infrastructure automation, configuration management and Infrastructure as Code using Ansible and related tools.
• Embed privacy, access control, security, compliance and responsible AI practices, including human approval where appropriate.
• Promote effective monitoring, logging, performance improvement and production troubleshooting.
• Communicate architectural decisions clearly and support teams in delivering consistent, high-quality solutions.

You will bring

• Experience designing and implementing enterprise AI, machine learning, cloud or DevOps solutions.
• Strong understanding of AI and machine learning architecture, deep learning, large language models and modern AI applications.
• Proficiency in Python and practical experience with PyTorch or TensorFlow.
• Experience with prompt engineering, Retrieval-Augmented Generation, embeddings, vector databases, model integration and performance optimization.
• Knowledge of AI agent frameworks, workflow orchestration, tool calling, API integration and the Model Context Protocol.
• Hands-on experience with Git, Ansible, CI/CD design, Python or Bash scripting, JSON and YAML. GitLab experience is an advantage.
• Familiarity with code quality and security tools, artifact repositories and container registries.
• Experience with AWS, Azure or Google Cloud, Docker, Kubernetes, microservices, networking and identity management.
• Knowledge of Ubuntu and Red Hat Enterprise Linux environments, monitoring, logging, observability and production support.
• Strong communication, collaboration and problem-solving skills, with the ability to work across technical and business teams.

"All academic credentials must be from recognized and accredited institutions and are further subject to verification."