Advisor, Software Development Engineering

Overview

Lead DevOps Engineer responsible for enabling engineering teams to build, test, secure, and deploy software across the full Software Development Life Cycle. The role designs CI/CD platforms, cloud-native infrastructure, developer productivity tooling, and AI-assisted workflows within cross-functional, distributed Agile teams.

What you'll do

• Play a lead role in designing and implementing software build and release technology solutions across multiple scrum teams and domains.
• Implement Continuous Integration and Continuous Delivery through automation and integration with developer tooling.
• Deliver DevSecOps best practices including CI/CD, SCM, and security practices.
• Perform regular demos to key stakeholders and consumers.
• Participate in and influence the development community and share knowledge and experience across the organisation.
• Maintain technical documentation and conduct training for Scrum teams on SCM and CI/CD tooling.
• Engage with Scrum teams and stakeholders to identify and prioritise gaps for backlog implementation.
• Participate in release planning, roadmap, and backlog grooming activities.
• Drive initiatives to improve delivery through DevOps and release-on-demand practices and ensure built-in quality in the SDLC.
• Help teams develop a DevOps culture focused on continuous improvement and customer value.
• Support the Release Manager and coordinate platform deployments.
• Assist with Change Management planning and weekly reviews.
• Assist with monthly OS patching coordination and validation.
• Apply GenAI tools to improve productivity, code quality, documentation, and analysis.
• Leverage ML, NLP, or AI automation to optimise workflows, testing, data analysis, or product development.
• Translate business problems into AI-driven use cases with measurable outcomes.
• Collaborate with cross-functional teams to integrate AI models, automation pipelines, or intelligent assistants into products.
• Ensure ethical AI usage, data governance compliance, and secure handling of model outputs.
• Stay updated with emerging AI technologies and recommend adoption strategies.

What you'll need

• Total experience of 8 to 13 years.
• Expert knowledge of CI/CD and associated tooling including Gitlab CI, Jenkins, Argo CD, Rundeck or similar.
• Expert knowledge of modern git-based Source Code Management platforms and git branching strategies such as Git-flow.
• Experience with observability tooling, ideally Dynatrace, including APM, Kubernetes monitoring, and service-level visibility.
• Extensive hands-on experience with cloud automation using Infrastructure as Code.
• Expertise in one or more programming languages such as Java, Python, Shell Scripting or similar.
• Experience with configuration management tooling including Terraform, Ansible or similar.
• Advanced working knowledge of secure coding practices, cybersecurity, vulnerability management, source code and artifact provenance, and associated tooling including OSA/SCA, SAST, DAST.
• Experience with Source Code Static Analysis and quality tools such as SonarQube.
• Hands-on production experience with Kubernetes microservices, from Docker image to deployment, ingress and Istio.
• Extensive experience with build automation across the complete project life cycle in an Agile environment.
• Experience with build management in a multi-platform distributed team.
• Experience with container and container orchestration technologies including Kubernetes.

Nice to have

• Be a DevOps advocate passionate about continuous improvement through process refinement and automation.
• Enjoy working with people and helping coach and encourage individuals and teams along the Agile/DevOps journey.
• Engage with and support teams in problem identification and decision-making.
• Be meticulous, with the ability to capture technical detail accurately.
• Leverage personal experience and detailed knowledge of build, release management, and engineering fundamentals to provide creative solutions.
• Have excellent verbal and written communication skills to support effective communication with all stakeholders.
• Be able to report issues accurately and objectively.
• Be able to build effective stakeholder relationships up to and including programme directors.
• Be comfortable working to deadlines and achieving results under time pressure without compromising quality.
• Have experience using AI copilots for productivity and quality improvement.
• Be capable of writing effective prompts, verifying responses, and applying results.
• Understand AI concepts including LLMs, NLP, embeddings, RAG, automation, and model safety.
• Have hands-on experience with AI tools such as GitHub Copilot, Microsoft Copilot, OpenAI GPT models, Azure AI Studio, and AI testing tools.
• Be able to evaluate AI outputs for correctness, security, and bias.

Details

• Location: Pune, India.