NeerInfo Solutions
Role: Enterprise AI Architect (Senior Principal)
Employment Type: Permanent
Key Skills:
Architecture Governance, Business Process Design, Mapping, Capability Models, EA Frameworks, Reference Architecture, Research, Papers, Enterprise Roadmap / Strategy, Transformation.
Key Responsibilities AI Strategy & Architecture
Evaluate existing AI frameworks, platforms, and governance models to identify strengths, weaknesses, and gaps.
Align AI initiatives with business goals, data governance policies, and IT infrastructure.
Recommend enhancements to AI architecture, tools, and integration strategies.
Assess and propose suitable AI platforms, tools, and frameworks for enterprise adoption.
AI Solution Design
Develop end-to-end AI reference architectures including data models, agentic workflows, orchestration, security, and observability.
Design agentic flow architectures for autonomous task execution and business workflow transformation.
Architect AI agents for AIOps and intelligent operations.
Collaborate with engineering and operations teams to integrate AI solutions into enterprise systems.
Governance &Compliance
Ensure AI solutions comply with enterprise governance, security, and ethical standards.
Establish best practices for responsible AI and model explainability.
Define observability standards including tracing, logging, and performance monitoring using tools like LangFuse or Arize Phoenix.
Innovation & Thought Leadership
Stay abreast of emerging AI technologies and recommend adoption strategies.
Foster a culture of experimentation, learning, and responsible AI.
Mentor junior team members and aspiring architects.
Key Requirements for the Position
Proven experience in designing and implementing enterprise-grade AI solutions.
Expertise in building agentic systems and intelligent automation for operations and SDLC.
Strong understanding of AI governance, security, and compliance frameworks.
Experience in integrating AI with enterprise systems and external APIs.
Key Skills
Agent Frameworks & Orchestration:
LangGraph, LangChain, workflow design.
State & Memory Management:
Persistent state handling, vector databases (e.g., Pinecone, Weaviate, Chroma).
Tool Integration:
External APIs, enterprise systems, custom tools.
MLOps/LLMOps:
CI/CD for models, prompt versioning, lifecycle management.
Observability Tools:
LangFuse, Arize Phoenix.
Knowledge Fabric & AI Fabric:
Semantic modeling, contextual AI enablement, knowledge graphs.
Qualification Criteria
Bachelor’s or master’s degree in computer science, Data Science, AI/ML, or related field.
Minimum 10 years of experience in enterprise architecture, with at least 5 years in AI/ML solutioning.
Demonstrated experience in designing AI agents and intelligent automation solutions.
Strong communication, strategic thinking, and stakeholder management skills.
Ability to work cross-functionally and influence decision-making.
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Employment Type: Permanent
Key Skills:
Architecture Governance, Business Process Design, Mapping, Capability Models, EA Frameworks, Reference Architecture, Research, Papers, Enterprise Roadmap / Strategy, Transformation.
Key Responsibilities AI Strategy & Architecture
Evaluate existing AI frameworks, platforms, and governance models to identify strengths, weaknesses, and gaps.
Align AI initiatives with business goals, data governance policies, and IT infrastructure.
Recommend enhancements to AI architecture, tools, and integration strategies.
Assess and propose suitable AI platforms, tools, and frameworks for enterprise adoption.
AI Solution Design
Develop end-to-end AI reference architectures including data models, agentic workflows, orchestration, security, and observability.
Design agentic flow architectures for autonomous task execution and business workflow transformation.
Architect AI agents for AIOps and intelligent operations.
Collaborate with engineering and operations teams to integrate AI solutions into enterprise systems.
Governance &Compliance
Ensure AI solutions comply with enterprise governance, security, and ethical standards.
Establish best practices for responsible AI and model explainability.
Define observability standards including tracing, logging, and performance monitoring using tools like LangFuse or Arize Phoenix.
Innovation & Thought Leadership
Stay abreast of emerging AI technologies and recommend adoption strategies.
Foster a culture of experimentation, learning, and responsible AI.
Mentor junior team members and aspiring architects.
Key Requirements for the Position
Proven experience in designing and implementing enterprise-grade AI solutions.
Expertise in building agentic systems and intelligent automation for operations and SDLC.
Strong understanding of AI governance, security, and compliance frameworks.
Experience in integrating AI with enterprise systems and external APIs.
Key Skills
Agent Frameworks & Orchestration:
LangGraph, LangChain, workflow design.
State & Memory Management:
Persistent state handling, vector databases (e.g., Pinecone, Weaviate, Chroma).
Tool Integration:
External APIs, enterprise systems, custom tools.
MLOps/LLMOps:
CI/CD for models, prompt versioning, lifecycle management.
Observability Tools:
LangFuse, Arize Phoenix.
Knowledge Fabric & AI Fabric:
Semantic modeling, contextual AI enablement, knowledge graphs.
Qualification Criteria
Bachelor’s or master’s degree in computer science, Data Science, AI/ML, or related field.
Minimum 10 years of experience in enterprise architecture, with at least 5 years in AI/ML solutioning.
Demonstrated experience in designing AI agents and intelligent automation solutions.
Strong communication, strategic thinking, and stakeholder management skills.
Ability to work cross-functionally and influence decision-making.
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