Principal AI Architect
First seen by Alion on Aug 21, 2026.
Role : Principal AI Architect
We are seeking a highly experienced and visionary Principal AI Architect to design, lead, and implement enterprise-scale AI, Machine Learning, and Generative AI solutions. The ideal candidate will have strong expertise in building scalable AI platforms using Databricks, Snowflake, and cloud-native ecosystems, along with hands-on experience in Feature Engineering, RAG, LLMs, and Agentic AI architectures.
Key Responsibilities :
AI/ML and GenAI Architecture :
- Define end-to-end architecture for AI/ML and Generative AI systems.
- Design scalable Lakehouse-based AI platforms using Databricks and Snowflake.
- Architect solutions supporting batch and real-time inference workloads.
- Design enterprise-grade LLM, RAG, and Agentic AI applications.
- Establish architectural standards, best practices, and reusable AI frameworks.
RAG, LLM and Agentic AI :
- Design and implement Retrieval-Augmented Generation architectures using vector databases and knowledge pipelines.
- Architect intelligent AI agents for automation, orchestration, and decision-making workflows.
- Evaluate and integrate LLMs such as OpenAI and LLaMA.
- Optimize prompt engineering, embeddings, context management, scalability, accuracy, and cost.
- Develop enterprise-ready GenAI solutions.
Data and Feature Engineering :
- Design robust data pipelines for structured and unstructured data.
- Lead feature engineering strategies for ML and AI models.
- Collaborate with Data Engineering teams to build high-performance data ingestion and transformation pipelines.
- Implement data governance, lineage, and data quality frameworks.
Cloud and AI Platform Architecture :
- Architect AI solutions on AWS, Azure, or GCP.
- Design cloud-native and microservices-based AI systems.
- Leverage Docker and Kubernetes for scalable AI deployments.
- Implement MLOps and LLMOps best practices for CI/CD, monitoring, and lifecycle management.
Technical Leadership and Innovation :
- Conduct Proof of Concepts to validate architectural approaches and design decisions.
- Analyze existing product architecture and recommend AI-driven enhancements.
- Provide technical leadership and mentorship to AI, Data Science, and Engineering teams.
- Identify emerging AI and GenAI trends and enterprise adoption opportunities.
- Collaborate with product managers, stakeholders, and business leaders to translate business requirements into AI solutions.
Governance, Security and Compliance :
- Define AI governance frameworks including model monitoring and responsible AI practices.
- Ensure compliance with data privacy and enterprise security standards.
- Implement observability, model performance tracking, and risk mitigation strategies.
Required Skills and Qualifications :
- 12+ years of experience in AI/ML Architecture, Data Engineering, Advanced Analytics, or related areas.
- Strong expertise in Generative AI, LLMs, RAG, and Agentic AI architectures.
- Hands-on experience with Databricks, Snowflake, and Lakehouse architecture.
- Strong programming skills in Python and PySpark.
- Experience with TensorFlow, PyTorch, and Scikit-learn.
- Experience with Vector Databases such as FAISS, Pinecone, or Weaviate.
- Knowledge of MLOps and LLMOps tools such as MLflow, Kubeflow, or Azure ML.
- Experience designing real-time and batch AI pipelines.
- Strong understanding of Feature Engineering and model lifecycle management.
- Experience with REST APIs, microservices, and scalable system design.
- Strong knowledge of cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker and Kubernetes is preferred.
Skills
Artificial Intelligence, AI Architecture, Generative AI, RAG, LLM, Agentic AI, OpenAI, AWS, MLOps, PyTorch, Tensorflow