Senior AI Architect

Job Summary

We are seeking an experienced Senior AI Architect to design, develop, and implement scalable Artificial Intelligence (AI) and Machine Learning (ML) solutions that align with business objectives. The ideal candidate will have strong expertise in AI architecture, generative AI, large language models (LLMs), cloud platforms, data engineering, and enterprise AI integration. This role involves defining AI strategies, leading technical teams, establishing architecture standards, and delivering secure, reliable, and high-performance AI solutions.

Key Responsibilities

• Design and implement enterprise-level AI and ML architectures to support business requirements.

• Define AI strategy, technology roadmaps, architecture standards, and implementation best practices.

• Architect and deploy generative AI applications using LLMs, Retrieval-Augmented Generation (RAG), and vector databases.

• Develop AI-powered applications, intelligent automation solutions, and predictive analytics systems.

• Evaluate and select appropriate AI frameworks, models, platforms, and tools.

• Design scalable AI infrastructure using cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (Google Cloud Platform).

• Lead the development and deployment of machine learning models and AI services.

• Implement MLOps and LLMOps practices for model training, deployment, monitoring, versioning, and lifecycle management.

• Ensure AI solutions meet enterprise security, privacy, compliance, scalability, and performance requirements.

• Collaborate with business stakeholders, data scientists, software engineers, and product teams to translate business needs into technical solutions.

• Establish standards for responsible AI, model governance, explainability, fairness, and risk management.

• Optimize AI models and infrastructure for performance, reliability, and cost efficiency.

• Provide technical leadership, mentor engineering teams, and conduct architecture reviews.

• Integrate AI solutions with enterprise applications, APIs, databases, and existing business systems.

• Monitor emerging AI technologies and recommend innovations that provide measurable business value.

Required Technical Skills

• Strong experience in AI architecture, machine learning, deep learning, and enterprise software development.

• Proficiency in Python and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn.

• Hands-on experience with generative AI, LLMs, prompt engineering, and RAG architectures.

• Experience with vector databases and search technologies such as Pinecone, FAISS, Weaviate, Milvus, or Azure AI Search.

• Knowledge of AI development frameworks such as LangChain, LlamaIndex, or equivalent tools.

• Experience with cloud AI services, including AWS SageMaker, Amazon Bedrock, Azure AI Foundry, Azure Machine Learning, or Google Vertex AI.

• Understanding of data pipelines, data lakes, data warehouses, APIs, microservices, and distributed systems.

• Experience with Docker, Kubernetes, CI/CD, and infrastructure automation.

• Knowledge of MLOps/LLMOps, model monitoring, model evaluation, and deployment automation.

• Strong understanding of AI security, data privacy, governance, and responsible AI principles.

• Experience designing highly available, scalable, and cost-effective enterprise solutions.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

• Typically 12-15+ years of experience in software engineering, data science, machine learning, or AI-related roles.

• Significant experience designing and delivering production-grade AI/ML solutions.

• Demonstrated experience leading architecture design and enterprise technology initiatives.

• Strong analytical, problem-solving, communication, and stakeholder-management skills.

Preferred Qualifications

• Experience implementing enterprise generative AI and agentic AI solutions.

• Familiarity with multimodal AI, knowledge graphs, fine-tuning, and model optimization.

• Experience with enterprise security frameworks and regulatory compliance requirements.

• Relevant cloud architecture or AI certifications.

• Experience managing technical teams and working in Agile development environments.

Key Competencies

• Strategic thinking and enterprise architecture design.

• Technical leadership and team mentoring.

• Innovation and continuous improvement.

• Business and technology alignment.

• Risk assessment and decision-making.

• Cross-functional collaboration and communication.

Expected Deliverables

• Enterprise AI architecture blueprints and reference architectures.

• AI technology roadmaps and solution design documents.

• Production-ready AI and generative AI applications.

• Secure, scalable, and monitored AI deployment pipelines.

• AI governance, model evaluation, and operational standards.

• Technical documentation and architecture recommendations.

Success Metrics

• Reliability, scalability, and performance of deployed AI solutions.

• Accuracy, quality, and business effectiveness of AI models.

• Reduction in operational costs and manual effort.

• Adoption of AI solutions across business functions.

• Compliance with security, privacy, and governance standards.

• Time to deploy AI solutions and deliver measurable business value.