JD for GenAI Architect - AD
Location Offshore
Experience: Minimum 10+ years of experience in technology development or automation, with at least
5 - 7 years of experience in particularly generative AI technologies.
Key Skills:
Primary:
o 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
o Familiarity with any one or more cloud platforms (Azure, AWS, Google Cloud) external
certification preferred
o Experience in API integration and application development
o Design and Architecture - external certification preferred
o Data modelling and engineering
o Micro Services Architecture
o DevSecOps
o Strong problem-solving and analytical skills, with the ability to work collaboratively in
cross-functional teams
Secondary:
o Programming Language: Python and/or Java 11+ (such as Java 17, Java 21 & not just
Java 8) /.NET/Node.JS/React/Angular
o Experience on Applications Modernization with any public cloud
o Integration Design Patterns
o Familiarity with Machine learning frameworks (TensorFlow, PyTorch) is a plus
o Familiarity with RPA tools (UiPath, Automation Anywhere) is a plus
o Application Portfolio Rationalization (APR) and R Treatment Strategies is a plus
Responsibilities:
Define and oversee the execution of the organization's 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 company's 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 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
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
************************************************************************************************************************************
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:
o 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
o Familiarity with any one or more cloud platforms (Azure, AWS, Google Cloud) external
certification preferred
o Experience in API integration and application development
o Design and Architecture - external certification preferred
o Data modelling and engineering
o Micro Services Architecture
o DevSecOps
o Strong problem-solving and analytical skills, with the ability to work collaboratively in
cross-functional teams
Secondary:
o Programming Language: Python and/or Java 11+ (such as Java 17, Java 21 & not just
Java 8) /.NET/Node.JS/React/Angular
o Experience on Applications Modernization with any public cloud
o Integration Design Patterns
o Familiarity with Machine learning frameworks (TensorFlow, PyTorch) is a plus
o Familiarity with RPA tools (UiPath, Automation Anywhere) is a plus
o Application Portfolio Rationalization (APR) and R Treatment Strategies is a plus
Responsibilities:
Define and oversee the execution of the organization's 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 company's 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 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
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
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