JOB ESSENTIALS:

• translating the client’s business requirements into specific systems, applications or process designs with interlocked financial modeling for very large complex technical solutions.
• Analyzes customer service requirements and designs service solutions to meet those objectives.
• Primary expert to construct the specific solution, scope document, risk profile, and corresponding financials.
• Maintains and utilizes detailed industry and internal services knowledge in the construction of industry-leading services solutions, including expert working level knowledge of the processes, technologies, and people components involved in the services arena.
• Uses expertise to construct specific and detailed solutions that encompass process, technology, and staffing plans for customer sales opportunities. Constructs risk assessments and corresponding remediation plans relative to complex services proposals.
• Participates in the construction of detailed financial models that align with complex services proposals.
• Composes Statement of Work or other documents, using departmental automation tools as available, to craft detailed and accurate deliverables that specify processes, technology, staffing, and project management involved in proposed services solutions.
• As needed, provide a “trusted expert advisor” role as a Subject Matter Expert for technical services, to both internal and external customers, ranging from formal advice to internal and external customer presentations.
• Follow all organizational Standard Operating Procedures relative to cost modeling, approvals and reviews, and all other associated workflow and deliverables.

REQUIRED QUALIFICATIONS & SKILLS:

• 10 Years: experience architecting enterprise application solutions across on-premises and cloud infrastructure.
• 10 Years: architecting solutions in one or more of the cloud platforms: GCP, Azure, and AWS.
• 8 Years: developing cloud native application architectures across leading cloud platforms.
• 8 Years: architecting solutions that utilize fit-for-purpose service models such as IaaS, PaaS, and SaaS
• 8 Years: experience in all phases of Machine Learning, Artificial Intelligence and Deep Learning solutions using Azure or AWS or google technologies.
• 8 Years: Strong understanding of virtual networks, VPNs, DNS, load balancers, and firewalls.
• 8 Years: Understanding of cloud security frameworks, encryption, identity and access management (IAM), and compliance standards like GDPR, HIPAA, etc.
• 8 Years: Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code (IaC) tools like Terraform or CloudFormation.
• 8 Years: Knowledge of API design, development, and management, including RESTful and SOAP APIs.
• 8 Years: Knowledge of microservices, serverless architectures, and cloud-native application development.
• 8 Years: Excellent verbal and written communication skills to articulate cloud strategies and solutions to stakeholders.
• 6 Years: Experience with cloud-based AI/ML services. Examples are Azure Machine Learning, Cognitive Services or AWS SageMaker, Redshift, EC2, Data Pipeline, Kinesis, EMR, Transcribe or Google Cloud Vertex AI, Agent Builder and other AI/ML services.
• 1 Year: Cloud Certification eg * AWS Certified Solutions Architect, Azure Solutions Architect Expert or Google Professional Cloud Architect

• Design and maintain enterprise-level architecture that aligns with organizational goals and technical requirements.
• Develop scalable, secure, and resilient enterprise infrastructure, ensuring adherence to best practice.
• Evaluate current infrastructure and identify components for cloud migration, creating a detailed migration strategy including timelines and resource allocation.
• Implement and validate migration processes to ensure data integrity and system functionality.
• Ensure compliance of architecture with industry standards and regulatory requirements.
• Collaborate with stakeholders to understand business needs and translate them into technical solutions.
• Advise on AI/Machine Learning/Deep Learning and generative AI projects, mapping relevant Azure, Google, and AWS services.
• Analyze AI services to extract technical and business insights that inform reference architectures, runbooks, and training content.