GenAI Architect - SM

JD for GenAI Architect - SM

Location Offshore

Experience: Minimum 14+ years of experience in technology development or automation, with at least 1 - 3 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 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 organizations vision and strategy for generative AI technology, ensuring alignment with overall business objectives.
• Engage with senior executive leadership to establish and refine the companys 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 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 (eg, 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

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.
• DevOps / SRE : Knowledge of the DevOps best practices, tools landscape ability to propose relevant tech stack for any new engagement
• RFP support/exposure : Ability to support/drive SMALL/MEDIUM RFPs solution independently (incl. estimation and validation ) and collaborate in 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

DevOps
Jenkins, Git , Azure DevOps, SonarQube, JIRA, SonarLint