Ai Architect

Design and implement full-stack scalable AI/ML systems integrating frontend (React/Angular), backend (Python/Node.js), RESTful APIs, RAG and agentic frameworks (LangChain, AutoGen).
- Architect distributed, microservice-based AI pipelines using event-driven architectures and containerized deployments on Azure and AWS (secondary).
- Engineer prompt-based systems using retrieval-augmented generation (RAG), few-shot learning, and prompt tuning to optimize LLM performance.
- Lead data preprocessing workflows with Spark, Pandas, and MLFlow, including feature engineering and data augmentation.
- Model observability frameworks for drift detection, performance monitoring, and lifecycle management using tools like Prometheus and Grafana.
- Enforce AI/ML system security by integrating data protection protocols, implementing role-based access control (RBAC), encryption standards (TLS, AES), and ensuring compliance with regulatory frameworks such as GDPR, HIPAA, and ISO/IEC 27001 through automated policy enforcement and audit logging.
- Ensure AI security, governance through bias mitigation, explainability and secure deployment aligned with compliance standards.
- Conduct technical feasibility assessments, PoCs, and infrastructure cost estimation with risk analysis.
- Lead AI architecture with cross-functional collaboration, Agile execution, and continuous innovation while maintaining technical excellence and comprehensive documentation.
- Exceptional ability to articulate complex AI and technical concepts with clarity, enabling effective communication across technical and non-technical stakeholders.

**Qualifications**:

- Bachelor's or Master’s degree in Computer Science, Data Science, or related field with 10+ years in AI/ML architecture and enterprise-grade solution delivery.
- Over 5 years of specialized experience in architecting and deploying AI/ML systems, with a demonstrated history of delivering production-grade solutions across diverse use cases.
- Hands-on experience with agentic frameworks (LangChain, AutoGen), prompt engineering, and scalable LLM deployment.
- Strong expertise in GenAI, Machine Learning, Data Science, transformer models (GPT, BERT), deep learning (CNNs, RNNs, GANs), and multimodal AI systems.
- Proficient in Python and ML/DL frameworks like TensorFlow, PyTorch, Hugging Face, and MLFlow.
- Skilled in designing distributed AI pipelines using microservices, containerization (Docker, Kubernetes) and cloud platforms (Azure, AWS-secondary).
- Deep understanding of data engineering, CI/CD automation, model observability, and performance optimization.
- Specialized in AI security including adversarial robustness, federated learning, encryption standards, and regulatory compliance.
- Proven leadership in Agile environments, technical mentoring, and translating business needs into scalable AI architectures.
- Passionate about innovation with a track record of integrating emerging AI technologies into production-ready systems.

**Preferred Skills**:

- Proven experience in developing AI-powered solutions across industries.
- Strong understanding of MLOps practices, CI/CD pipelines, and Azure DevOps for scalable AI deployment.
- Solution Architect Certifications is plus advantage like AZ-305: Azure Solutions Architect Expert, AWS Certified Solutions Architect.
- Deep knowledge of secure and ethical AI design, including data privacy regulations and responsible AI principles.
- Demonstrated success in leading GenAI/ML projects from concept to production with measurable impact.
- Advanced problem-solving and analytical skills for translating complex challenges into efficient AI solutions.
- Excellent communication and collaboration abilities to bridge technical and non-technical stakeholders.
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- Pay: ₹9,012.33 - ₹63,624.49 per month

Work Location: In person