Sr. Java Full Stack Developer

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Sr. Java Full Stack Developer – Project Delivery Specialist you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.

Work you’ll do/Responsibilities  

Rationalize PCS service providers into a select set of strategic partners across Engineering and Cloud Security Services. Drive measurable value through cost optimization, improved productivity, enhanced customer experience, and simplified operations. Ensure delivery excellence with a focus on quality, speed, and innovation.

• Full Stack Development: Design, develop, and maintain high-quality, scalable, and robust full-stack applications and services using Python, Java, and/or Go.
• Cloud-Native Engineering: Build and deploy containerized (Docker, Kubernetes) and serverless applications on AWS and GCP, leveraging cloud-native services for compute, data, and messaging.
• Infrastructure as Code (IaC): Develop and manage cloud infrastructure using IaC principles and tools such as Terraform and Ansible to ensure automated, repeatable, and secure environment provisioning.
• Operational Excellence (SRE): Embrace a "you build it, you run it" philosophy. Take ownership of the entire lifecycle of your services, including automated testing, deployment, monitoring, and operational support. Proactively identify and resolve root causes of issues to ensure service reliability and performance.
• Risk & Control Management: Adhere to Citi's technology standards and risk management frameworks. Identify, assess, and mitigate risks in your designs and code, ensuring all solutions are compliant with security policies and data regulations.
• CI/CD & Automation: Implement and maintain CI/CD pipelines to automate the build, test, and deployment processes, enabling rapid and efficient delivery of new features and fixes.
• Collaboration & Code Quality: Actively participate in code reviews and adhere to the Developer Manifesto principles, including owning your code, writing meaningful commit messages, and maintaining a clean and tidy repository. Collaborate across teams to promote reuse and reduce duplication.
• Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
• Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

The Team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Qualifications

Required

• 7+ years of experience in software, systems, or embedded engineering.
• 7+ years of experience working Java/J2EE
• 7+ years of experience developing or deploying AI solutions, custom hardware, or high-performance platforms.
• 7+ years of experience with Linux internals, device drivers, and kernel or embedded systems programming.
• Strong proficiency in one or more of the following programming languages: Python, Java, GoStrong understanding of AI/ML frameworks (PyTorch, TensorFlow, ONNX) and performance/model optimization.
• Hands-on experience with public cloud platforms, specifically AWS and/or Google Cloud (GCP).
• Containerization Technologies: Expertise in Docker and container orchestration platforms like Kubernetes