GenAI Architect

Experience:

Key Skills:

• Primary:

• GenAI Skills:

• Deep expertise in generative AI algorithms and models, including commercial and open source LLM models,
• Agentic AI, Agent Architectures, Prompting patterns, LLMOps, MLOps, AI Guardrails, RAG patterns, GenAI Frameworks (such as LangChain and LlamaIndex)
• Code Companions (Understanding & appreciation of any 1 or 2 code Companion tool GHCP, Amazon Q Developer, Tabnine, cursor.ai, IBM WatsonX etc.) – any external certification preferred
• GenAI Strategies and Implementation
• Familiarity with any one cloud platforms (Azure, AWS, Google Cloud) – external certification preferred
• Experience in API integration and application development
• Design and Architecture - external certification preferred
• Micro Services Architecture
• DevOps
• Strong problem-solving and analytical skills, with the ability to work collaboratively in cross-functional teams
• Secondary:
• Programming Language: Python or Java 11+ (such as Java 17, Java 21 & not just Java 8) /.NET/Node.JS/React/Angular
• Experience on Applications Modernization with any public cloud
• Integration Design Patterns

Responsibilities:

• Define and oversee the execution of the organization's vision and strategy for generative AI technology, ensuring alignment with overall business objectives.
• Engage with senior executive leadership to establish and refine the company's generative AI roadmap for cutting-edge initiatives.
• Spearhead the evaluation and strategic integration of state-of-the-art generative AI technologies, frameworks, and methodologies to maintain competitive advantage.
• Cultivate a culture of excellence in innovation, fostering an environment that supports groundbreaking research and development within the generative AI space.
• Oversee the development and deployment of sophisticated generative AI models and algorithms, ensuring they provide transformative solutions to critical business challenges.
• Set and uphold rigorous standards in data practices, model development, and algorithm performance to optimize efficiency and effectiveness.
• Act as a principal technical advisor, enriching the organization's knowledge base and fostering an environment where mentorship and professional development are paramount.
• Articulate complex generative AI concepts and project statuses to a range of stakeholders, ensuring clarity and alignment across technical and non-technical audiences.
• Remain at the cutting edge of generative AI, machine learning, and broader technological developments, translating insights into strategic opportunities.
• Proactively identify and address potential risks in generative AI projects, including ethical considerations, regulatory compliance, and data governance.
• Work in close coordination with legal, compliance, and ethical teams to ensure that generative AI practices meet the highest standards of integrity and societal impact.
• Prompt Development: Design, test, and refine prompts to optimize large language model (LLM) performance (e.g., GPT-4, BERT). Tailor prompts for specific applications like customer support, content generation, or virtual assistants or specific customer use cases as needed
• Use Case Development: Work with stakeholders to develop prompts and AI models that meet business goals and user needs.
• Lead AI Initiatives: Architect and develop large-scale AI models for natural language understanding, text generation, and creative content generation
• AI Integration & Automation: Integrate AI services (Azure, AWS, Google Cloud, OpenAI) into existing systems to streamline workflows and automate processes
• Research & Innovation: Stay informed on the latest advancements in NLP and LLMs. Experiment with new methodologies, share insights, and propose innovative approaches to enhance AI capabilities