Principal AI Architect

• The Principal AI Architect will lead the design and implementation of enterprise-grade AI systems and intelligent applications.
• This role is responsible for defining scalable AI architectures, building production-ready AI platforms, and driving innovation across LLM applications, multi-agent systems, retrieval architectures, and real-time AI services.
• The ideal candidate will possess deep expertise in AI/ML engineering, cloud platforms, and modern AI orchestration frameworks while collaborating closely with product, data science, and platform engineering teams.

Requirement/Must Have:

• 12+ years of hands-on experience in AI/ML engineering and data science with strong production delivery experience.
• Deep expertise in LLM application development, including LangChain, LangGraph, RAG, prompt engineering, embeddings, and tool-calling agents.
• Proven experience architecting and deploying multi-agent AI systems and hybrid retrieval architectures.
• Strong expertise in Python, SQL, FastAPI, Docker, CI/CD pipelines, and cloud platforms such as AWS and Google Cloud Platform.
• Experience with vector databases, knowledge graphs, Neo4j, FAISS, and enterprise AI deployment platforms.
• Strong understanding of AI performance optimization, latency reduction, hallucination mitigation, and scalable inference systems.
• Experience working in regulated industries with compliance awareness such as SOX, GDPR, or SOC 2.
• Strong communication skills with the ability to explain technical concepts to business stakeholders.

Experience:

• 12+ years of AI/ML engineering and data science experience.
• Hands-on experience delivering enterprise AI products and customer-facing AI solutions.
• Experience with real-time inference APIs, hybrid retrieval systems, and production AI telemetry.
• Experience with AI frameworks such as CrewAI, AutoGen, Google ADK, and LangGraph.
• Experience with machine learning models including XGBoost, NLP, deep learning, time-series forecasting, and causal inference.

Responsibilities:

• Design and implement enterprise AI system architectures including multi-agent orchestration, RAG pipelines, hybrid retrieval systems, and inference APIs.
• Define technical blueprints covering data ingestion, embeddings, response generation, evaluation, and monitoring.
• Build production-quality AI services, APIs, and reusable AI framework components.
• Develop AI retrieval pipelines, chunking systems, and agent orchestration modules.
• Optimize AI systems for latency, accuracy, precision/recall trade-offs, and cost efficiency.
• Own AI deployment pipelines, Docker-based deployments, CI/CD automation, and production telemetry.
• Evaluate emerging AI technologies, frameworks, and market trends to influence strategic AI roadmaps.
• Collaborate with Product, Data Science, and Platform Engineering teams to align AI architecture with business objectives.
• Provide technical leadership and architectural guidance across AI initiatives.
• Communicate architecture decisions, trade-offs, and business impacts to technical and non-technical stakeholders.

Should Have:

• Experience with Snowflake Cortex or similar enterprise LLM platforms.
• Experience contributing to open-source AI/ML tools or publishing technical content.
• Prior experience in enterprise SaaS, fintech, or AI consulting organizations.
• AI certifications such as AWS Certified Machine Learning Engineer or Google Cloud Platform Professional ML Engineer.
• Master s or PhD in Computer Science, Statistics, Operations Research, or related quantitative field.

Skills:

• Python
• SQL
• LangChain
• LangGraph
• RAG Architecture
• Prompt Engineering
• Embedding Pipelines
• FastAPI
• Docker
• AWS
• Google Cloud Platform
• BigQuery
• FAISS
• Neo4j
• CI/CD
• AI/ML Engineering
• NLP
• Deep Learning
• Hybrid Retrieval Systems
• Multi-Agent Systems
• Knowledge Graphs

Qualification And Education:

• Master s or PhD in Computer Science, Operations Research, Statistics, or a related quantitative field.
• AWS Certified Machine Learning Engineer or Google Cloud Platform Professional ML Engineer certification preferred.