Cloud AI Engineer and Cloud AI Architect

The successful candidate will be responsible for leading the practice’s ambitious growth initiative with our most strategic cloud partner – Microsoft Azure or Amazon Web Services or Google Cloud Platform or IBM Cloud. This opportunity is scoped for high performing, high potential subject matter experts who are self-directed, entrepreneurial, highly collaborative, organized, diligent, and thoughtful. This role requires a domain expertise combined with the ability to task-organize, focus on the details, and sustain and drive progress over time.

For the right candidate, this role offers an opportunity to contribute to rapid revenue growth in one of the most exciting and dynamic segments of the market. This is an ideal opportunity for technologists seeking cross vertical and/or cross industry expertise. Among other career-enhancing considerations, this role provides opportunities to directly and indirectly manage teams.

The entire AIA leadership team is personally committed to the success of the AI architects and engineers on-boarded through this focused cloud hiring initiative.

Principal Responsibilities

- Design and Implement Artificial Intelligence and Data Science solutions on Cloud at enterprise scale.

- Contextual understanding of customer requirements with visions, strategies, and roadmaps for implementation

- Collaboration with solution architect, business analysts and partner architects/stakeholders in Global Delivery model for AI Solution development

- Contribute to the Cognizant cloud community by developing assets, cross-training, learning echo-system.

Technical Qualifications

- Hands-on programming skill on at least one language – C#.net or node.js or python.

- Expert on Cloud competencies on “Artificial Intelligence” and “Machine Learning” PaaS components:

· Contextual Conversation design (Azure BOT service/Amazon Lex/ Google Dialog flow) – for personalized and humanized interaction with end user for complex business cases

· Natural Language Processing model - design, training and publishing for multiple languages

· Emotion and Sentiment Analytics

· Custom Speech model - Speech-to-text and Voice synthesis calibrated for language, accent, pitch, tone, noise and business vocabs.

· Computer vision - OCR, Face Recognition, Custom model for Object detection and classifications

· Document/Form Entity Extraction

· Cognitive Search on heterogeneous unstructured data

· Enterprise Channel Integration for AI through Direct line

· Deployment and publish for AI and ML services with ACR, ACI, Docker, Azure Kubernetes

· Azure/ AWS/ GCP/ Watson certifications on AI & Data Science like AI 102, DP 100.

- (Optional) Holistic knowledge of Solution Architecture, including “Data Analytics”, “Security”, “Dev Ops” & “ML Ops”:

· Enterprise cloud Data repository –Cloud Storage, NoSQL DB, Graph DB, Data Lake

· Data Ingestion, Transformation, Analytics – Real-time and batches

· Enterprise Security for AI/ML - Active Directory - Authentication, Authorization

· Web app and services – Micro services, Azure functions, Logic apps, API management

· DevOps CI/CD pipeline on Cloud – “Github for Enterprise”

- Ability to compare and contrast across technologies in any layer objectively with evaluation criteria and considerations

- Excellent communication skills, preparing PowerPoint presentations, executive readouts