We are looking for a versatile DevOps Engineer to design, build, and operate the automation backbone of our platform. You will own CI/CD pipelines, infrastructure automation, and the integration of

AI-driven capabilities into our engineering workflows. The ideal candidate blends solid hands-on

DevOps skills (Ansible, Jenkins, Python) with a working knowledge of APIs and emerging AI engineering practices.

What You'll Do

- Design, build, and maintain CI/CD pipelines using Jenkins (declarative pipelines, shared libraries,

multi-branch workflows).
- Develop infrastructure-as-code and configuration management with Ansible (playbooks, roles,

dynamic inventories, Ansible Vault).
- Write robust automation tooling and scripts in Python for provisioning, orchestration, monitoring,

and remediation.
- Build and consume REST/GraphQL APIs to integrate internal and third-party systems, orchestrate

services, and enable self-service tooling.
- Integrate AI/ML capabilities into engineering workflows — e.g., LLM-assisted automation, intelligent

alerting, prompt engineering, and RAG-based internal tools.
- Automate build, test, release, and deployment processes to reduce manual effort and increase delivery

velocity.
- Implement observability: logging, metrics, tracing, and alerting for services and pipelines.
- Champion security and reliability best practices (secrets management, least-privilege access, automated

compliance checks).
- Collaborate with development, QA,



and security teams to continuously improve the delivery lifecycle.

Required Skills & Experience

- 5+ years of hands-on DevOps / Site Reliability / Automation engineering experience.
- Strong expertise with Ansible for configuration management and automation.
- Proficiency in Python for scripting, tooling, and automation.
- Solid experience with Jenkins and CI/CD pipeline design.
- Practical API knowledge — designing, consuming, testing, and securing RESTful APIs (auth, rate

limiting, versioning).

PUBLIC

- Experience with version control (Git) and branching/release strategies.
- Familiarity with Linux systems administration and shell scripting.
- Understanding of containerization and orchestration (Docker, Kubernetes) — a plus.
- Cloud experience (AWS, Azure, or GCP) — a plus.

AI Engineering Experience

- Exposure to AI/LLM engineering concepts: prompt engineering, model APIs (OpenAI, Anthropic,

Azure OpenAI, etc.), embeddings, and RAG pipelines.
- Ability to integrate AI services via APIs into automation and operational tooling.
- Interest in applying AI to DevOps: predictive scaling, anomaly detection, automated incident response,

and ChatOps.

Nice to Have

- Infrastructure-as-Code with Terraform.
- Experience with monitoring stacks (Prometheus, Grafana, ELK).
- Knowledge of security automation and vulnerability management workflows.
- Familiarity with message queues / event-driven architectures.

📌 DevOps Engineer (Automation, AI & API Integration) (India)
🏢 Principle Pride
📍 India