AI/Gen AI Solution Architect - LLM

• Lead end-to-end AI/GenAI solution architecture from discovery to enterprise-scale deployment.

• Design scalable AI/ML and GenAI systems including:

• LLM-based applications

• Retrieval-Augmented Generation (RAG) patterns

• Agentic workflows

• Define high-level and low-level designs (HLD/LLD), integration architectures, and deployment strategies.

• Create reference architectures, technical blueprints, and operational runbooks.

• Conduct customer discovery workshops to identify high-value use cases.

• Define business outcomes, KPIs, and success metrics.

• Act as a trusted advisor to stakeholders and executives.

• Clearly communicate architecture options, trade-offs, risks, costs, and timelines.

• Embed Responsible AI principles across all solutions:

• Governance frameworks

• Security and privacy controls

• Compliance and regulatory adherence

• Implement safeguards including:

• Content moderation and safety

• PII protection mechanisms

• Auditability and traceability

• Model risk management

• Design human-in-the-loop systems for critical decision-making workflows.

• Partner with engineering teams to translate architecture into execution plans.

• Define development standards, best practices, and reusable frameworks.

• Guide implementation across:

• APIs and microservices

• CI/CD pipelines

• Cloud-native architectures

• Provide technical leadership across:

• Cloud platforms (AWS, Azure, GCP)

• MLOps / LLMOps frameworks

• Observability and monitoring

• FinOps and cost optimization

• Ensure scalability, reliability, and performance of AI systems in production.

• 10+ years of experience in solution architecture or related roles.

• Strong expertise in AI/ML and Generative AI technologies.

• Hands-on experience with LLMs, RAG architectures, and modern AI frameworks.

• Proven experience with cloud platforms (AWS, Azure, or GCP).

• Deep understanding of microservices, APIs, and distributed systems.

• Experience implementing MLOps / LLMOps practices.

• Strong knowledge of security, governance, and compliance in AI systems.

• Excellent communication and stakeholder management skills, including executive-level interactions.

• Experience with enterprise-scale AI transformations.

• Familiarity with AI governance frameworks and regulatory standards.

• Background in designing agent-based or autonomous AI systems.

• Certifications in cloud or AI/ML domains.

• AI/ML Architecture

• Generative AI (LLMs, RAG, Agents)

• Cloud Architecture

• MLOps / LLMOps

• API & Microservices Design

• Security & Responsible AI

• Stakeholder Communication

• Strategic Thinking

Astra North Infoteck Inc.