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Lead Solution Architect
1 week ago
As a Solution Architect, you are expected to deliver the following:
- As an architect work closely with delivery teams and other stakeholders to provide technical leadership, drive architectural decisions, shape deals and propositions, create plans and roadmaps, and produce design & architectural artifacts by delving into client’s unique challenges.
- Collaborate with other team members and SMEs as required to define the solution. Drive a solution from conception to close using standard solution architecture processes, and modeling tools to drive quality. Understand and leverage different pricing models and work with Sales Leads to articulate deal pricing.
- Engage in early conversations with the client and/or sales team, support origination and deal qualification, and become a trusted advisor. Prepare and represent the solution in Deal Reviews and support Orals, Client Presentations, and negotiation discussions with key client buyers.
- The AI Solution Architect is a mix of the traditional Solution Architect and AI Engineer roles. In this critical capacity, you will address complex business issues using state-of-the-art Data Processing, Generative AI, and advanced machine/deep learning techniques.
- You will refine your specialized skills to design, develop, and implement strategic AI architecture solutions, playing a key role in seamlessly integrating these technologies into existing enterprise frameworks.
- Leveraging a structured approach to Architecture projects using existing methodologies (e.g., Waterfall, Agile, Iterative) that make use of existing reference architecture and established architectural styles and design patterns.
- Strong understanding of On-prem and cloud architectural patterns and migration strategies
- As a senior member, you will provide coaching and mentoring to motivate and inspire more junior colleagues from within your team and across the organization.
- Ability to estimate sizing requirements for hardware (e.g. server specs) and services for any solution based on developed solution design, architecture, data storage, and processing requirements.
Key Skills
- Experience engaging in consulting engagements (including estimation models, scoping, development of budgetary estimates, and writing proposals as a response to RFPs)
- Deep knowledge of solution architecture with an emphasis on Data Processing, AI applications, including awareness of LLM models.
- Experience working with stakeholders to create technical visions, high-level architectures, and delivery roadmaps for projects.
- Capability in creating design artifacts and presenting them for approval at architectural forums attended by multi-disciplined stakeholders from engineering to senior client executives.
- Experience in designing and delivering large-scale Data solutions using relevant approaches (Lakehouse, Data Mesh, Cloud Scale Analytics, etc.)
- Identifying and designing for key architectural characteristics such as performance, security, and reliability
- Skills in designing data models and architectures that support large-scale AI applications.
- An ability to articulate architectural differences between solution methods and the challenges and approaches to integrating solutions built on different platforms.
Subject matter expertise in some of the following Areas:
- Machine Learning, Deep Learning (Computer Vision, NLP, and LLM) production implementations and design patterns.
- Modern Data Strategy frameworks and Architectures
- Ability to leverage solution building blocks: Microsoft Fabric, Azure Synapse, SQL, Databricks, Python, .Net / Azure frameworks, and other databases including NoSQL databases such as Vector and Graph Databases
- Ability to integrate and deliver analytical visualizations using a wide variety of BI software like PowerBI, Tableau, Spotfire, Looker, and Grafana but not limited to.
- Ability and experience in deploying AI models to edge-based architecture and orchestration from central monitoring systems.
- Awareness and knowledge of OT-IT integration with a focus on Digitalization and AI use cases.
- Knowledge and experience of AutoML and MLOps for orchestration and easy management/deployment of AI solutions.
- Awareness of Data & Analytics complete insights – Redshift, Snowflake, Teradata, SAGE Maker, Big Query, Hadoop, etc.
- Awareness of core OSS AI DL frameworks – PyTorch, TensorFlow
- Strong leadership skills for managing diverse teams and conducting effective customer engagements.
- Exceptional communication and presentation skills to effectively convey complex AI concepts and solutions.
Education and Qualifications
- 8-11 Years of experience related to key skills, roles, and responsibilities in solution architectures with end-to-end design, implementation, and deployment of Digital & AI solutions.
- A bachelor’s or master’s degree in computer science, Engineering, or a related field. Preferably with a focus on artificial intelligence, machine learning, or data science