Principle Engineer - Software Development

What you'll be doing...

As a Principal Engineer in Verizon Business Group, you'll be working on our VBG team to develop exciting new technologies at the forefront of the

customer experience. You will be a key member of the team responsible for developing and managing cutting-edge AI-powered platforms, applications, and bots that serve Verizon's diverse business customer base.

You will be responsible for:

• Architecture Design: Designing end-to-end AI solutions on GCP as an architect. Integrating CCAI and Gemini 1.5 for advanced conversational AI applications.
• Technical Leadership: Providing technical guidance and mentorship to engineering teams on best practices for developing and deploying AI models and pipelines on GCP.
• Solution Development: Leading the development of scalable and robust AI solutions, including data ingestion, pre-processing, model training, deployment, and monitoring.
• CCAI Integration: Integrating Google CCAI capabilities into contact center solutions, leveraging Gemini 1.5 for enhanced natural language understanding and dialogue management.
• Generative AI Expertise: Utilizing Gemini 1.5 to develop and deploy generative AI models for tasks such as text generation, code generation, and creative content creation.
• Performance Optimization: Optimising AI models and pipelines for performance, scalability, and cost-efficiency on GCP.
• Research & Innovation: Demonstrating constant know-how of latest advancements in AI, particularly in the areas of generative AI and large language models, and exploring their potential applications within our business.
• Designing, developing, and implementing innovative AI solutions leveraging Google Gemini 1.5, Google CCAI, and Google Cloud Platform.
• Building and enhancing applications and bots for optimizing sales and service functions across various business segments.
• Conducting development and maintenance of a robust ReactJS/Python GUI-based platform and microservices backend.
• Migrating & transforming existing applications to leverage the latest technologies and architectural patterns.
• Driving the adoption of new solutions, leading proof-of-concept initiatives, and contributing to the overall architectural direction.
• Collaborating closely with the CCAI platform team to integrate Verizon platform features and leverage new functionalities.
• Defining end-to-end architecture for enterprise-grade applications using cutting-edge technologies.
• Designing, developing, and implementing scalable and pluggable React/Node/AWS-based applications.
• Troubleshooting and resolving technical issues through debugging, research, and investigation.
• Demonstrating a comprehensive understanding of the entire web and bot development lifecycle (design, development, and deployment).
• Investigating and resolving production issues.
• Evaluating, recommending, and implementing new technologies while maintaining existing systems.
• Designing and developing reusable frameworks and components.
• Analysing and resolving technical and application-related challenges.
• Utilizing DevOps tools such as Git, Jira, Confluence, and Jenkins throughout the development lifecycle.
• Optimizing applications for maximum speed and scalability.
• Collaborating effectively with developers , web designers , business stakeholders to enhance application usability.
• Writing secure code adhering to best practices and minimizing vulnerabilities.

Where you'll be working

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

What you should have:

• Bachelor's degree or four or more years of work experience.
• Six or more years of relevant work experience.
• Experience in architecting and implementing end-to-end solutions using CCAI, ReactJS, Node.js, microservices, data modelling, Proficiency in Python or another suitable programming language for AI development.
• Proven experience as an AI Architect or a similar role, with a strong track record of designing and implementing AI solutions on GCP.
• Deep understanding of Google Cloud AI Platform, including services like Vertex AI, AutoML, and AI Platform Pipelines.
• Hands-on experience with Google CCAI, including agent design, dialogue flow creation, and integration with contact center platforms.
• Strong knowledge and experience with generative AI models, particularly Gemini 1.5 or similar large language models.
• Good understanding of Generative AI and Large Language Model (LLM) concepts, including their workings, strengths, limitations, and common use cases. Familiarity with prominent LLM models such as OpenAI, Gemini, and Vertex AI. Good knowledge of prompt engineering techniques for optimizing LLM performance.
• Proficiency in manipulating and analysing data from different sources (cloud and on-premise), at different scales (big data and small data), and of different formats
• Must have excellent coding proficiency with demonstrated expertise in python, java, R, etc.
• Knowledge of a variety of AI/ML models, frameworks(keras, pytorch, etc.) and libraries/packages/apis (e.g., scikit)
• Demonstrate ability to explain both the code and the underlying math used in algorithms/models.
• Experience with model deployment in production environments a big plus
• Familiarity with hypothesis testing, sampling, and causal inference methods
• Proven experience in developing, delivering, and operating large-scale public and cloud-based solutions in a multi-tenant environment.
• Strong understanding of DevOps principles and practices.
• Expertise in developing, deploying, and debugging cloud-based applications, particularly on Google Cloud Platform.
• Proficiency in containerization technologies (e.g., Docker) and their application in the development process.
• Experience working in Agile/Scrum development methodologies.
• Solid understanding of secure coding practices and principles.
• Proficiency in code versioning tools like Git and CI/CD tools such as Jenkins and GitLab.

Even better if you have one or more of the following:

• Knowledge of AWS, Kubernetes, Elasticsearch, and PostgreSQL.
• Experience with security domain concepts and best practices.
• Understanding of pipelines and EKS (CI/Helm/CD).