Solution Architect - CI Process Automation
We are assisting our client with their search for a technical expert in automation to join their team in Bangalore. Our client is seeking an experienced and highly skilled CI Process Automation Solution Architect to lead the design and implementation of intelligent, automated Continuous Integration (CI) and engineering process solutions. This role will drive transformation across DevOps, CI/CD pipelines, engineering productivity, and AI‑enabled automation initiatives. The ideal candidate will combine deep technical expertise in CI/CD ecosystems, hands‑on development experience, strong architectural skills, and applied data and AI/ML knowledge to modernize software delivery processes in a small but rapidly growing team.
Key Responsibilities
- Design and architect scalable, secure, and resilient CI/CD frameworks across multi‑cloud and hybrid environments.
- Standardize and optimize build, test, release, and deployment automation.
- Define enterprise CI/CD best practices, governance models, and reusable automation frameworks.
- Improve build reliability, pipeline performance, and deployment frequency.
- Evaluate, select, and implement enterprise DevOps and automation tooling and low‑code/no‑code ecosystems and platforms.
- Drive adoption of modern CI platforms such as Azure DevOps and CircleCI.
- Ensure secure DevSecOps integration.
- Collaborate with Enterprise Architecture, Cloud and Security teams to ensure alignment with standards.
- Act as the technical authority for CI automation initiatives within the organization.
- Partner with global engineering teams, business analysts, and functional leaders to drive transformation roadmaps.
- Mentor DevOps engineers and automation teams.
- Conduct architecture reviews and ensure adherence to standards.
Required Qualifications
- Bachelor’s or Master’s degree in a relevant field.
- 10+ years of experience in DevOps, CI/CD, or Software Engineering.
- 5+ years in architecture or technical leadership roles.
- Deep expertise in CI/CD platforms.
- Strong scripting/programming skills.
- Experience with containerization and orchestration.
- Hands‑on experience with cloud platforms (Azure, GCP).
- Proven experience implementing DevSecOps practices.
- Experience integrating AI/ML solutions into engineering workflows.
Preferred Qualifications
- Experience with MLOps platforms and AI model lifecycle management.
- Familiarity with LLM integration frameworks and developer AI copilots.
- Knowledge of observability platforms (Prometheus, Grafana, ELK, Datadog).
- Relevant certifications (Azure Architect, Kubernetes, DevOps).
Key Competencies
- Enterprise architecture mindset.
- Strategic thinking with execution focus – “Hands on”.
- Start‑up mindset and mentality.
- Strong stakeholder management skills.
- Data‑driven decision making.
- Innovation and continuous improvement mindset.