Job highlights

- any external certification preferred . GenAI Strategies and Implementation .
- Familiarity with any one or more cloud platforms (Azure,AWS,Google Cloud) external certification preferred .
- Experience on Applications Modernization with any public cloud . .

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 setting 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

📌 GenAI Architect - AD (Hubballi)
🏢 Han Digital Solution
📍 Hubballi