GenAI Architect - AD

JD for GenAI Architect - AD Location Offshore Experience: Minimum 17+ years of experience in technology development or automation, with at least 5 - 7 years of experience in particularly generative AI technologies. 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 or more cloud platforms (Azure, AWS, Google Cloud) external certification preferred Experience in API integration and application development Design and Architecture - external certification preferred Data modelling and engineering Micro Services Architecture DevSecOps Strong problem-solving and analytical skills, with the ability to work collaboratively in cross-functional teams Secondary : Programming Language: Python and/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 Familiarity with Machine learning frameworks (TensorFlow, PyTorch) is a plus Familiarity with RPA tools (UiPath, Automation Anywhere) is a plus Application Portfolio Rationalization (APR) and R Treatment Strategies is a plus Responsibilities: Define and oversee the execution of the organizations vision and strategy for generative AI technology, ensuring alignment with overall business objectives and driving industry leadership. Engage with senior executive leadership to establish and refine the companys generative AI roadmap, securing buy-in and resources 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. Establish robust partnerships with leading research institutions, tech companies, and industry thought leaders to enhance organizational capabilities and knowledge. Drive collaboration among various teams, including AI research scientists, data engineers, product managers, and business units, to ensure seamless execution of generative AI projects. 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 organizations 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 Process Automation & Collaboration: Define automation needs, troubleshoot issues, and implement intelligent automation using RPA tools (UiPath, Automation Anywhere). Key Areas of Expertise: Proficiency : (1-Learner, 2-Practitioner, 3-Specialist, 4-Expert) Hands-on : Predominant hands-on experience on Any programming language stack, minimum 2-5 years on either Azure & AWS cloud; Minimal 1 2-year experience in application modernization or development using GenAI related skillset Architecture Styles/Patterns : Knowledge & vast experience with traditional architectures, Minimum 1-2 years experience in Microservices cloud native, event-driven architectures & design patterns NFR understanding, QoS tactics : Ability to articulate and provide examples from his/her prior work; Experience in Application Performance Management, and Application Security (Vulnerability remediation, OWASP Top 10 understanding, etc.) App Modernization : Has prior experience with APR and cloud migration; Knowledge of R treatment strategies and can provide examples from his/her prior work; Working knowledge or experience with Java & Spring Boot upgrades or .NET upgrades is preferred. DevSecOps / SRE : Knowledge of the DevSecOps best practices, tools landscape & ability to propose relevant tech stack for any new engagement RFP support/exposure : Experience & ability to support/drive SMALL/MEDIUM RFPs solution independently (incl. estimation and validation ) and collaborate in COMPLEX RFPs Communication : Prior experience in client facing roles, good verbal communication skills with stakeholders Important Key Words in Resume Search: GenAI Amazon-Q, GHCP , LLMs, Prompt Engineering , LangChain, LangGraph, ChatGPT , Gemini, BART, RAG Web JSP, Angular , React , Jasmine (Karma runner) , Node.js , Websockets Data Hibernate , Spring LDAP, Spring Integration, Spring Data ( JPA , MongoDB , CouchDB, Cassandra, Dynamo, elastic search, Neo4J, REDIS, HADOOP, JDBC), NPM Data Modules, Vector DB Platform & Services Java , .NET, Python , Map reduce, Advanced Data Structures, Crytography, REST, Spring Boot, Microservices, Spring Integration, JUnit, NUnit Cloud AWS , Azure, GCP , PCF, Docker, Kubernates DevSecOps Jenkins, Git , Azure DevOps, DevSecOps, SonarQube, JIRA, SonarLint