AI Architect- Associate Director

Job Title: Associate Director

Role: Senior AI Architect

Experience: 13 - 16 Years

About the Role

We are seeking a Senior AI Architect with deep expertise in Generative AI (GenAI) , Retrieval-Augmented Generation (RAG) , Agentic AI systems, Python, API development, System Design, MLOps, and production-grade AI/ML solution architecture . This role involves architecting and leading AI solutions , driving innovation, and mentoring junior engineers. You will work closely with business and technical stakeholders to deliver scalable, production-grade AI systems.

Key Responsibilities

• Experience architecting end-to-end AI/ML solutions including model selection, inference design, data pipelines, evaluation strategy, monitoring, governance, and lifecycle management.
• Design and optimize RAG pipelines leveraging advanced retrieval strategies and vector databases.
• Build and integrate Agentic AI frameworks for autonomous workflows and decision-making at scale.
• Define architecture patterns for reusable AI components, services, APIs, and platforms.
• Design and develop REST APIs for AI/ML model serving and application integration.
• Build scalable API services using frameworks such as FastAPI , Flask , or similar.
• Design architectures that address: Scalability, Availability, Latency, Reliability, Fault tolerance, Security, Cost optimization, Maintainability, Observability.
• Define MLOps/LLMOps processes for model versioning, prompt versioning, evaluation pipelines, model registry, and production monitoring.
• Working knowledge of Docker, Kubernetes, CI/CD, model deployment , model versioning, monitoring, logging, rollback strategy, and production support.
• Experience designing and deploying cloud-native AI solutions on Azure, AWS, or GCP. Azure experience with Azure OpenAI, Azure ML, Azure AI Search, AKS, Blob Storage, Key Vault, and Application Insights is preferred.
• Define best practices for model performance, scalability, and reliability in production environments.
• Collaborate with leadership to shape AI strategy , roadmap, and technical standards.
• Mentor and guide junior engineers on AI/ML development and deployment.
• Ensure compliance with ethical AI principles and security standards.

Required Skills

• Programming & Software Engineering: Expert-level proficiency in Python , with strong software engineering fundamentals including modular design, testing, logging, exception handling, performance optimization, and production-grade development.
• Generative AI: Proven experience with Agentic AI solutions, RAG, fine-tuning, and deployment in production.
• Agentic AI: Hands-on experience with agentic AI frameworks such as LangChain, AutoGen, Semantic Kernel , or similar, with understanding of production-grade agent orchestration.
• API Development & System Design: Strong experience in REST API development, microservices, scalable architecture, AI/ML model-serving APIs, and enterprise system design .
• Cloud & MLOps: Experience with AWS, Azure, or GCP , along with MLOps/LLMOps practices including CI/CD, Docker, Kubernetes, model deployment, monitoring, versioning, and rollback.
• Strong leadership, communication, and stakeholder management skills.

Preferred Skills

• Exposure to advanced agent orchestration , tool calling, workflow automation, multi-agent patterns, and guardrails for safe execution.
• Familiarity with data engineering concepts such as ETL/ELT, SQL/NoSQL, Spark, Databricks, metadata management, and unstructured data pipelines .

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• 13 - 16 years of experience in AI/ML development, with at least 5 years in Generative AI and advanced AI systems .

Job Title: Associate Director

Role: Senior AI Architect

Experience: 13 - 16 Years

About the Role

We are seeking a Senior AI Architect with deep expertise in Generative AI (GenAI) , Retrieval-Augmented Generation (RAG) , Agentic AI systems, Python, API development, System Design, MLOps, and production-grade AI/ML solution architecture . This role involves architecting and leading AI solutions , driving innovation, and mentoring junior engineers. You will work closely with business and technical stakeholders to deliver scalable, production-grade AI systems.

Key Responsibilities

• Experience architecting end-to-end AI/ML solutions including model selection, inference design, data pipelines, evaluation strategy, monitoring, governance, and lifecycle management.
• Design and optimize RAG pipelines leveraging advanced retrieval strategies and vector databases.
• Build and integrate Agentic AI frameworks for autonomous workflows and decision-making at scale.
• Define architecture patterns for reusable AI components, services, APIs, and platforms.
• Design and develop REST APIs for AI/ML model serving and application integration.
• Build scalable API services using frameworks such as FastAPI , Flask , or similar.
• Design architectures that address: Scalability, Availability, Latency, Reliability, Fault tolerance, Security, Cost optimization, Maintainability, Observability.
• Define MLOps/LLMOps processes for model versioning, prompt versioning, evaluation pipelines, model registry, and production monitoring.
• Working knowledge of Docker, Kubernetes, CI/CD, model deployment , model versioning, monitoring, logging, rollback strategy, and production support.
• Experience designing and deploying cloud-native AI solutions on Azure, AWS, or GCP. Azure experience with Azure OpenAI, Azure ML, Azure AI Search, AKS, Blob Storage, Key Vault, and Application Insights is preferred.
• Define best practices for model performance, scalability, and reliability in production environments.
• Collaborate with leadership to shape AI strategy , roadmap, and technical standards.
• Mentor and guide junior engineers on AI/ML development and deployment.
• Ensure compliance with ethical AI principles and security standards.

Required Skills

• Programming & Software Engineering: Expert-level proficiency in Python , with strong software engineering fundamentals including modular design, testing, logging, exception handling, performance optimization, and production-grade development.
• Generative AI: Proven experience with Agentic AI solutions, RAG, fine-tuning, and deployment in production.
• Agentic AI: Hands-on experience with agentic AI frameworks such as LangChain, AutoGen, Semantic Kernel , or similar, with understanding of production-grade agent orchestration.
• API Development & System Design: Strong experience in REST API development, microservices, scalable architecture, AI/ML model-serving APIs, and enterprise system design .
• Cloud & MLOps: Experience with AWS, Azure, or GCP , along with MLOps/LLMOps practices including CI/CD, Docker, Kubernetes, model deployment, monitoring, versioning, and rollback.
• Strong leadership, communication, and stakeholder management skills.

Preferred Skills

• Exposure to advanced agent orchestration , tool calling, workflow automation, multi-agent patterns, and guardrails for safe execution.
• Familiarity with data engineering concepts such as ETL/ELT, SQL/NoSQL, Spark, Databricks, metadata management, and unstructured data pipelines .

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• 13 - 16 years of experience in AI/ML development, with at least 5 years in Generative AI and advanced AI systems .

Job Title: Associate Director

Role: Senior AI Architect

Experience: 13 - 16 Years

About the Role

We are seeking a Senior AI Architect with deep expertise in Generative AI (GenAI) , Retrieval-Augmented Generation (RAG) , Agentic AI systems, Python, API development, System Design, MLOps, and production-grade AI/ML solution architecture . This role involves architecting and leading AI solutions , driving innovation, and mentoring junior engineers. You will work closely with business and technical stakeholders to deliver scalable, production-grade AI systems.

Key Responsibilities

• Experience architecting end-to-end AI/ML solutions including model selection, inference design, data pipelines, evaluation strategy, monitoring, governance, and lifecycle management.
• Design and optimize RAG pipelines leveraging advanced retrieval strategies and vector databases.
• Build and integrate Agentic AI frameworks for autonomous workflows and decision-making at scale.
• Define architecture patterns for reusable AI components, services, APIs, and platforms.
• Design and develop REST APIs for AI/ML model serving and application integration.
• Build scalable API services using frameworks such as FastAPI , Flask , or similar.
• Design architectures that address: Scalability, Availability, Latency, Reliability, Fault tolerance, Security, Cost optimization, Maintainability, Observability.
• Define MLOps/LLMOps processes for model versioning, prompt versioning, evaluation pipelines, model registry, and production monitoring.
• Working knowledge of Docker, Kubernetes, CI/CD, model deployment , model versioning, monitoring, logging, rollback strategy, and production support.
• Experience designing and deploying cloud-native AI solutions on Azure, AWS, or GCP. Azure experience with Azure OpenAI, Azure ML, Azure AI Search, AKS, Blob Storage, Key Vault, and Application Insights is preferred.
• Define best practices for model performance, scalability, and reliability in production environments.
• Collaborate with leadership to shape AI strategy , roadmap, and technical standards.
• Mentor and guide junior engineers on AI/ML development and deployment.
• Ensure compliance with ethical AI principles and security standards.

Required Skills

• Programming & Software Engineering: Expert-level proficiency in Python , with strong software engineering fundamentals including modular design, testing, logging, exception handling, performance optimization, and production-grade development.
• Generative AI: Proven experience with Agentic AI solutions, RAG, fine-tuning, and deployment in production.
• Agentic AI: Hands-on experience with agentic AI frameworks such as LangChain, AutoGen, Semantic Kernel , or similar, with understanding of production-grade agent orchestration.
• API Development & System Design: Strong experience in REST API development, microservices, scalable architecture, AI/ML model-serving APIs, and enterprise system design .
• Cloud & MLOps: Experience with AWS, Azure, or GCP , along with MLOps/LLMOps practices including CI/CD, Docker, Kubernetes, model deployment, monitoring, versioning, and rollback.
• Strong leadership, communication, and stakeholder management skills.

Preferred Skills

• Exposure to advanced agent orchestration , tool calling, workflow automation, multi-agent patterns, and guardrails for safe execution.
• Familiarity with data engineering concepts such as ETL/ELT, SQL/NoSQL, Spark, Databricks, metadata management, and unstructured data pipelines .

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• 13 - 16 years of experience in AI/ML development, with at least 5 years in Generative AI and advanced AI systems .