𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐚𝐥 𝐀𝐈/𝐌𝐋 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭

Role Summary

We are looking for a Principal AI/ML Architect

with strong hands-on experience designing and implementing enterprise AI/ML solutions. This role requires a combination of architecture leadership, machine learning, Generative AI, and cloud expertise

.

The ideal candidate will be a hands-on technical contributor

who actively works on AI/ML projects end-to-end — defining architecture, designing solutions, developing and integrating components, building production-grade implementations, troubleshooting issues, and supporting deployment and operationalization — while also providing technical leadership to the broader engineering team.

Key Responsibilities

• Architect, design, and implement end-to-end AI, ML, and Generative AI solutions

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• Translate business requirements into scalable, secure, and production-ready technical solutions.

• Actively develop and integrate solutions using Python, AI/ML frameworks, APIs, and cloud services

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• Design and implement solutions using LLMs, RAG, embeddings, vector search, agentic AI, and model orchestration

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• Build and operationalize capabilities for model training, deployment, inference, evaluation, monitoring, and lifecycle management

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• Implement MLOps/LLMOps

  practices including CI/CD, model and prompt versioning, automated testing, observability, and monitoring.

• Evaluate AI models, frameworks, platforms, and technologies and select appropriate solutions based on project requirements.

• Design and implement integrations across AI services, enterprise applications, APIs, data platforms, and cloud services.

• Ensure solutions meet enterprise requirements for security, privacy, scalability, performance, reliability, and cost optimization

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• Provide technical leadership through solution design, hands-on implementation, code reviews, troubleshooting, and mentoring.

Required Skills & Experience

• 8+ years of hands-on AI/ML experience

  , with proven end-to-end implementation experience and deep expertise in architecting, developing, and delivering production-grade AI/ML solutions at enterprise scale

  .

• Strong hands-on development experience with Python

  and modern software engineering practices.

• Strong experience across Machine Learning, Deep Learning, NLP, and Generative AI/LLMs

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• Hands-on experience with RAG, embeddings, vector databases/search, prompt and context engineering, and LLM evaluation

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• Strong experience with at least one major cloud platform: Azure, AWS, or GCP

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• Hands-on experience with MLOps/LLMOps, model deployment, monitoring, CI/CD, containers, and APIs/microservices

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• Experience working with structured and unstructured data, data pipelines, and enterprise data platforms

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• Strong understanding of AI security, privacy, Responsible AI, and enterprise governance

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• Strong communication skills with the ability to work effectively across engineering, architecture, product, and business teams.