AI Architect

Job summary

We are seeking an experienced AI Architect to design & deliver scalable, secure, & production-ready agentic AI solutions across Cyient.

The role will translate business requirements into enterprise ai architectures, define technology standards & reusable patterns, evaluate emerging AI technologies, & provide technical leadership from ideation through production and scale.

Key responsibilities

• Design end-to-end architectures for AI/ML, generative AI, LLM, & agentic AI solutions across enterprise environments.
• Translate business use cases & requirements into scalable AI solution architectures, including data flows, models, APIs, integrations, infrastructure, security, & governance.
• Architect enterprise AI solutions using LLMs, rag, embeddings, vector databases, prompt engineering, tool/function calling, model routing, & LLM orchestration.
• Design AI agent & multi-agent architectures, including agent planning, memory, tools, orchestration, human-in-the-loop, & enterprise system integration.
• Define AI/ML architecture covering model development, training, inference, deployment, monitoring, & lifecycle management.
• Evaluate & recommend foundation models, AI platforms, frameworks, vector databases, model-serving technologies, & cloud services based on performance, cost, scalability, security, & business requirements.
• Establish AI reference architectures, reusable frameworks, design patterns, engineering standards, & accelerators.
• Ensure AI solutions address responsible AI, security, privacy, compliance, access control, prompt injection, data leakage, hallucination, & model misuse.
• Define AI evaluation & observability approaches covering accuracy, relevance, groundedness, latency, cost, safety, reliability, & model/agent performance.
• Conduct technology assessments, prototypes, & POCs to evaluate emerging technologies including generative AI, agentic AI, multimodal AI, reasoning models, & AI infrastructure.
• Provide architectural guidance & mentorship to AI engineers, ML engineers, data scientists, & development teams, & participate in architecture governance & reviews.
• Collaborate with business leaders, enterprise architecture, solution architecture, data, cybersecurity, cloud, & engineering teams to ensure successful AI adoption & production deployment.

Key qualifications

• Bachelor's or master's degree in computer science, AI, data science, engineering, or related discipline.
• 10+ years of experience in software engineering, solution architecture, AI/ML, data science, or related technology domains, with 5+ years designing & implementing enterprise AI solutions.
• Strong hands-on experience with generative AI, LLMs, foundation models, rag, vector databases, embeddings, prompt engineering, LLM orchestration, & AI evaluation.
• Demonstrated experience designing production-grade AI & agentic AI solutions.
• Strong python programming skills & familiarity with modern AI/ML frameworks.
• Strong foundation in software architecture, distributed systems, APIs, microservices, databases, enterprise integration, & cloud architecture.
• Experience with one or more major cloud platforms such as Azure, AWS or google cloud.
• Experience with AI/ML deployment, model serving, monitoring, MLOps/LLMOps, & lifecycle management.
• Strong understanding of AI security, responsible AI, data privacy, and AI governance.
• Ability to evaluate emerging AI technologies and translate them into practical, scalable enterprise architectures.
• Strong communication, stakeholder-management, technical leadership, and mentoring skills.