1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Embed with client infrastructure and engineering teams to design, execute, and operationalize end-to-end infrastructure transformations.
- Own production outcomes including platform reliability, time-to-value, adoption, and scalability.
- Move ambiguous infrastructure problems to validated architectures and production-ready deployments through rapid iteration.
- Execute hands-on application migrations using rehost, re-platform, and redeployment strategies.
- Architect and implement network and security foundations including Zero Trust, SASE/SSE, micro-segmentation, container security, and AI governance.
- Design and govern architectures across compute, platform engineering, internal developer platforms, Kubernetes, CI/CD pipelines, networking, security, storage, containers, databases, applications, and AI platforms.
- Build data and AI foundations for structured and unstructured data and deploy AI platform layers for enterprise-scale workloads.
- Modernize relational and NoSQL databases through migration, schema conversion, performance tuning, and cloud-native deployment.
- Use Python for infrastructure automation, deployment scripting, data pipeline engineering, and AI agent development.
- Translate architecture into business impact for CTO, CFO, and CISO stakeholders and shape modernization roadmaps and AI adoption strategies.
- Create reusable patterns, playbooks, proofs of concept, and accelerators while enabling client teams to operate and extend the platforms independently.
Requirements
- A minimum of 12 years of experience is required.
- At least 2 years of experience with AI platform ecosystems, including AWS, Azure, GCP, open-source model deployment, and infrastructure for reliable enterprise AI workloads.
- Three to five years of engineering experience with cloud-native systems and experience deploying AI use cases.
- At least 1 year of experience designing, deploying, and operating AI platforms and infrastructure in production enterprise environments.
- More than 10 years of infrastructure engineering experience across cloud platforms, networking, security, Kubernetes, containerization, platform engineering, and enterprise applications.
- Demonstrated ownership and delivery of infrastructure transformation outcomes inside live enterprise environments.
- Ability to connect infrastructure decisions to business and financial outcomes.
- Experience presenting to and building trust with CTO, CFO, or CISO-level stakeholders.
- Strong problem-solving skills and flexibility to work in a 24/7 environment.
- Non-linear profiles with demonstrated delivery experience and outcome ownership are welcomed.
Categories
Forward Deployed
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.