Sr. enterprise architect

Sr. enterprise architect Job Summary

• Location: Noida
• Project role: Sr. enterprise architect
• Qualification: B-Tech
• Experience: >11 Years
• Skills: Python
• Secondary Skills:
  • TensorFlow
  • PyTorch
  • LangChain
  • ML modelling
  • Big Data Technologies
• No. of positions: 9

GEN AI Solution Director
Job Role Overview: As a Generative AI Solution Director, you will be responsible for leading the development and implementation of innovative AI solutions that leverage generative models to solve complex business problems. You will work closely with cross-functional teams, including data scientists, engineers, product managers, and business stakeholders, to ensure the successful delivery of AI-driven projects.

Key Responsibilities:

• Strategic AI Solution Design: Collaborate with business leaders and product managers to understand business requirements, pain points, and opportunities where AI can deliver significant value. Design end-to-end AI/ML solution architectures, including data pipelines, model development frameworks, deployment strategies, and integration with existing enterprise systems. Develop architectural blueprints, technical specifications, and detailed design documents for AI/ML initiatives.
• Technology Selection & Evaluation: Research, evaluate, and recommend appropriate 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 cloud, on-premises, or hybrid deployment models, considering scalability, performance, cost-effectiveness, security, and maintainability. Stay abreast of the latest advancements in AI/ML, Generative AI (LLMs, diffusion models), and related emerging technologies, assessing their potential impact and applicability.
• Technical Leadership & Guidance: Provide technical leadership and architectural guidance to data science, ML engineering, and software development teams throughout the entire AI/ML lifecycle (experimentation, development, deployment, monitoring). Ensure adherence to architectural principles, coding standards, best practices in model development, versioning, testing, and validation. Conduct architectural reviews and provide constructive feedback to ensure solution integrity and quality.
• Data Architecture & Management: Work closely with data engineers and data governance teams to design robust data architectures that support AI/ML initiatives, ensuring data quality, accessibility, security, and ethical handling. Understand and influence data collection, storage, processing, and feature engineering strategies relevant to AI/ML models.
• Scalability, Performance & Security: Design AI solutions that are highly scalable, performant, resilient, and secure, capable of handling large datasets and high inference volumes. Implement robust security measures and privacy-by-design principles in all AI architectures.
• Ethical AI & Compliance: Champion responsible AI practices, ensuring that all AI solutions are developed and deployed ethically, addressing considerations such as fairness, bias mitigation, transparency, and explainability. Ensure compliance with relevant data privacy regulations (e.g., GDPR, CCPA) and industry-specific standards.
• Stakeholder Communication: Effectively communicate complex technical AI concepts and architectural decisions to both technical and non-technical stakeholders (including executive leadership). Manage expectations, present progress, and articulate the business value and ROI of AI solutions.

• A bachelor's or master's degree or equivalent in computer science, Artificial Intelligence, or related field.
• AI development and architecture, with a focus on generative AI solutions specifically focused on designing and implementing AI/ML solutions in an enterprise environment.
• Proven expertise in designing and deploying end-to-end machine learning pipelines.
• Strong understanding of various AI/ML techniques and algorithms (e.g., supervised, unsupervised, etc.).