Principal AI/ML Architect( 8 yrs)

Job Description: *Principal AI/ML Architect*

Experience: 8+ Years

Work Mode: Remote – Pan India

Working Hours: 11:00 AM – 9:00 PM IST

Budget: ₹1.5 LPM

Employment Type: Contractual 7 months to 1 year

Immediate joiner required , no dual candidate, BGV mandatory after selection

Role Overview We are looking for an experienced Principal AI/ML Architect with strong hands-on expertise in designing, developing, and implementing enterprise-scale AI/ML and Generative AI solutions.

The ideal candidate will combine solution architecture leadership with hands-on technical expertise across Machine Learning, Deep Learning, LLMs, RAG, Agentic AI, Python, and cloud platforms.

The candidate must have proven experience delivering end-to-end, production-ready AI solutions, covering architecture, development, deployment, monitoring, and operationalization.

This role requires a hands-on technical leader who can translate business requirements into scalable, secure, and cost-effective AI solutions while mentoring engineering teams and driving technical excellence.

Key Responsibilities

• Architect, design, and implement end-to-end AI, ML, and Generative AI solutions.
• Translate business requirements into scalable, secure, and production-ready technical architectures.
• Develop and integrate AI/ML solutions using Python, modern AI/ML frameworks, APIs, and cloud services.
• Design and implement solutions involving LLMs, Retrieval-Augmented Generation (RAG), embeddings, vector databases, semantic search, and Agentic AI.
• Implement model orchestration, prompt engineering, context engineering, and LLM evaluation strategies.
• Build and operationalize model training, deployment, inference, monitoring, evaluation, and lifecycle management capabilities.
• Implement MLOps/LLMOps practices, including CI/CD pipelines, model and prompt versioning, automated testing, observability, and monitoring.
• Evaluate AI models, frameworks, tools, and cloud platforms based on business and technical requirements.
• Integrate AI services with enterprise applications, APIs, data platforms, and cloud infrastructure.
• Ensure AI solutions meet enterprise standards for security, privacy, scalability, performance, reliability, and cost optimization.
• Troubleshoot complex technical issues and optimize AI/ML application performance.
• Provide technical leadership through architecture reviews, hands-on implementation, code reviews, and engineering team mentoring.
• Ensure compliance with Responsible AI principles, enterprise governance, and data protection standards.

Required Skills And Experience

• 8+ years of hands-on AI/ML experience, with proven expertise in architecting, developing, and delivering production-grade enterprise AI/ML solutions.
• Strong programming expertise in Python and modern software engineering practices.
• Strong knowledge of Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI/LLMs.
• Hands-on experience with RAG, embeddings, vector databases/vector search, prompt engineering, context engineering, and LLM evaluation.
• Experience designing and implementing Agentic AI solutions and LLM orchestration.
• Strong experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Hands-on experience with MLOps/LLMOps, model deployment, monitoring, CI/CD, and model lifecycle management.
• Experience with containers, APIs, microservices, and production application integration.
• Knowledge of structured and unstructured data, data pipelines, and enterprise data platforms.
• Strong understanding of AI security, data privacy, Responsible AI, and enterprise governance.
• Excellent problem-solving, communication, stakeholder management, and technical leadership skills.

Key Expectations

• Proven ability to deliver AI/ML solutions end-to-end, from architecture to production deployment.
• Strong balance of hands-on coding and solution architecture.
• Ability to design scalable, secure, maintainable, and cost-efficient AI systems.
• Experience collaborating with cross-functional teams across engineering, architecture, product, and business functions.
• Ability to mentor engineers and establish best practices in AI solution development.

Mandatory Documentation and Background Verification (BGV)

• Background Verification (BGV) is mandatory.
• Candidates must submit all required documents and valid identity proofs for verification.
• Complete documentation is mandatory to proceed with the onboarding process.

Skills: ml,principal,ai