AI/Gen AI Solution Architect - LLM

Job Title:
AI / GenAI Solution Architect - LLM
Role Overview:
We are seeking an experienced AI / GenAI Solution Architect to lead end-to-end design and delivery of enterprise-grade AI and Generative AI solutions. This role combines deep technical expertise with strong customer engagement, driving innovation from discovery through large-scale adoption.
Key Responsibilities:
1. Solution Architecture & Design
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.
2. Customer Engagement & Advisory
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.
3. Responsible AI & Governance
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.
4. Engineering Collaboration & Delivery
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
5. Platform & Operational Excellence
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.
Required Qualifications:
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.
Preferred Qualifications:
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.
Key Skills:
AI/ML Architecture
Generative AI (LLMs, RAG, Agents)
Cloud Architecture
MLOps / LLMOps
API & Microservices Design
Security & Responsible AI
Stakeholder Communication
Strategic Thinking