Description

Lead the architecture, design, and technical roadmap for enterprise AI and AI-native solutions. This role owns the translation of business requirements into scalable architectures across data, model, and application layers.

This role is on-site.

Responsibilities

• Design and deliver enterprise-grade AI solutions, including reusable reference architectures and design patterns.
• Evaluate and integrate latest AI models and LLMs, leveraging cloud platforms like Azure AI, AWS, or Google Cloud.
• Define non-functional requirements for performance, security, reliability, scalability, and observability.
• Conduct technical reviews, PoCs, and feasibility assessments for emerging AI use cases.
• Collaborate with data engineers, MLOps teams, and product stakeholders to drive production-grade delivery.

Required Skills

• 15+ years of experience in software engineering with strong focus on AI/ML solution architecture.
• Hands-on expertise with machine learning, deep learning, and LLM-based solutions.
• Deep understanding of data architecture, including pipelines, feature stores, and MLOps.
• Experience with application integration via APIs, microservices, and event-driven architectures.
• Proficiency in creating HLDs, LLDs, sequence diagrams, and data flow documentation.
• Strong knowledge of CI/CD pipelines and MLOps tools.
• Experience with Docker and Kubernetes for cloud-native deployments.
• Ability to work effectively in Agile environments with distributed teams.

Preferred Skills

• Experience with vector databases, semantic search, RAG, and knowledge graphs.
• Knowledge of AI governance, responsible AI, and model risk management.
• Familiarity with integrating AI solutions into ERP and CRM systems.

Key Skills

Education

Bachelor's or Master's degrees