Job Family
Architecture / Design
No. of Positions
4
Job Description (Posting)
Job Summary: The AI Solution Architect will be responsible for translating complex business challenges into viable, scalable, and secure AI/ML solutions. This role requires a deep understanding of AI/ML methodologies, data architectures, cloud platforms, and software engineering best practices. The successful candidate will work closely with business stakeholders, data scientists, ML engineers, software developers, and IT operations teams to architect, guide, and ensure the successful delivery of AI-powered products and services.
Key Responsibilities:
- Strategic AI Solution Design: Collaborate with business leaders and product managers to understand requirements, pain points, and opportunities for AI. Design end-to-end AI/ML solution architectures, including data pipelines, model development frameworks, deployment strategies, and integration with existing systems. Develop architectural blueprints, technical specifications, and detailed design documents.
- Technology Selection & Evaluation: Research, evaluate, and recommend AI/ML technologies, platforms, frameworks, tools, and services (e.g., TensorFlow, PyTorch, scikit-learn, AWS SageMaker, Azure ML, Google AI Platform, MLOps tools). Make informed decisions regarding deployment models, considering scalability, performance, cost, security, and maintainability. Stay updated on latest AI/ML advancements and assess their applicability.
- Technical Leadership & Guidance: Provide architectural guidance to data science, ML engineering, and software development teams throughout the AI/ML lifecycle. Ensure adherence to architectural principles, coding standards, and best practices. Conduct architectural reviews and provide feedback to ensure solution quality.
- Data Architecture & Management: Work with data engineers and governance teams to design robust data architectures supporting AI initiatives, ensuring data quality, security, and ethical handling. Influence data collection, storage, processing, and feature engineering strategies.
- Scalability, Performance & Security: Design solutions that are scalable, performant, resilient, and secure, capable of handling large datasets and high inference volumes. Implement security measures and privacy-by-design principles.
- Ethical AI & Compliance: Promote responsible AI practices, ensuring solutions are developed ethically, addressing fairness, bias, transparency, and explainability. Ensure compliance with data privacy regulations like GDPR and CCPA.
- Stakeholder Communication: Effectively communicate complex AI concepts and architectural decisions to technical and non-technical stakeholders. Manage expectations, present progress, and articulate business value and ROI.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, AI, Engineering, or related field.
- (X+) years of experience in solution architecture, with at least (Y+) years focused on AI/ML solutions in an enterprise environment.
- Proven expertise in designing and deploying end-to-end machine learning pipelines.
Qualification
B.E, B-Tech, MTech (Master of Technology)
Employee Group
Business Line FT
City
Dallas
Entity
CSW
Auto req ID
BR
Expected Date of Closure
25-Aug-2025
Pay Range Minimum
Pay Range Maximum
Skill (Primary)
Data Science-Advanced Analytics-Python
Skill Level 3 (Secondary Skill 1)
Data Science-Artificial Intelligence-LangChain
Skill Level 3 (Secondary Skill 2)
Cloud Services-Platform Engineering-Artificial Intelligence
Skill Level 3 (Secondary Skill 3)
Cloud Services-Platform Engineering-Big Data Technologies
Skill Level 3 (Secondary Skill 4)
Tools and Standards (ERS)-Big Data-Kafka
Skill Level 3 (Secondary Skill 5)
Technical Skills-Open Source-Spark
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