Solution Architect with Generative AI/LLM

Key Responsibilities:

• Lead and mentor a team of engineers in the design and development of foundational frameworks and infrastructure to support advanced analytics and GenAI solutions.
• Architect and implement scalable, reusable infrastructure components for data processing, integration, and enterprise-wide AI/ML initiatives.
• Define and drive integration strategies for both analytical applications and GenAI models, including Large Language Models (LLMs) and Agentic AI, into core enterprise systems and frameworks.
• Collaborate with platform, data, and ML teams to define data pipelines and infrastructure for model training, deployment, and monitoring, with a focus on both analytics and GenAI.
• Ensure solutions are technically robust, aligned with enterprise architecture, and meet scalability, performance, and reliability requirements.
• Actively participate in the design, development, and maintenance of high-performance applications using Java, Python, JavaScript, Scala, PySpark, Spark, and Snowflake.
• Work extensively with AWS services, including designing and deploying serverless or containerized solutions using ECS, Lambda, S3, Glue, and other cloud services.
• Develop and deploy microservices-based and event-driven architectures using modern frameworks to support modular and scalable application development.
• Integrate and work with GenAI frameworks and APIs such as OpenAI, Hugging Face, Google Vertex AI, or other enterprise-grade platforms.
• Establish and enforce coding standards, conduct peer code reviews, and ensure best practices for test automation and CI/CD workflows.
• Ensure security compliance through vulnerability detection, remediation, and implementation of OWASP best practices in the application lifecycle.
• Collaborate with Agile cross-functional teams, including Product Owners, QA, and DevOps, for sprint planning, delivery, and continuous improvement