AI Solutions Architect

The ideal candidate to lead the design and implementation of AI-driven systems and platforms. The candidate will be responsible for aligning AI technologies with business goals, architecting robust and scalable solutions, and guiding development teams through delivery. This role bridges technical expertise with strategic thinking.

Roles and Responsibilities

• Lead the architecture and design of AI/ML-powered solutions across multiple domains: NLP, Computer Vision, Predictive Analytics, and Generative AI.
• Collaborate with stakeholders to define AI-driven strategies aligned with business goals.
• Select appropriate models, frameworks, and platforms (TensorFlow, PyTorch, OpenAI, Azure AI, etc.).
• Design end-to-end AI workflows: data pipelines, model training, evaluation, deployment, and monitoring.
• Provide technical leadership and mentorship to AI developers, engineers, and data scientists.
• Ensure model performance, scalability, and maintainability through best practices.
• Integrate AI systems with APIs, microservices, and cloud infrastructure.
• Promote ethical and responsible AI use, including bias detection and governance.

Eligibility & Skills Educational Qualification:

• B.E./B.Tech/M.Tech in Computer Science, Data Science, or related field.
• Certifications in AI/ML architecture or cloud AI (AWS, Azure, GCP) preferred.

Technical Skills

• Proven experience in designing and deploying AI/ML solutions at scale.
• Deep understanding of ML lifecycle, model evaluation, and feature engineering.
• Hands-on expertise with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Knowledge of Generative AI, LLMs, LangChain, RAG, and vector databases.
• Strong experience with cloud AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
• Data engineering and pipeline skills (Airflow, Spark, Kafka).
• Strong system architecture and integration experience (REST APIs, microservices, Docker, Kubernetes).
• Excellent communication and stakeholder management skills.

Preferred Skills

• Prior experience as ML/AI Lead or Senior Data Scientist.
• Knowledge of enterprise data governance and compliance.
• Industry expertise in retail, fintech, healthcare, or other AI-intensive sectors.