Gen AI Architect

Job Title: Gen AI Architect

Location: US, Remote

JD: Experience Level:
15+ years overall experience in technology and digital engineering, with 5+ years of hands-on experience in AI/ML, with at least 3+ years in Agentic AI, Generative AI (LLMs, RAG, multimodal, agentic systems).

Role Overview:
The Gen AI Architect North America will to lead the design, architecture, and delivery of enterprise-grade AI solutions powered by Large Language Models (LLMs), multi-modal AI, and Retrieval-Augmented Generation (RAG) pipelines. The ideal candidate will combine deep technical expertise in AI/ML systems with proven experience in enterprise architecture, ensuring solutions are scalable, secure, compliant, and aligned with business goals.
This role involves defining the technical roadmap for Generative AI initiatives, selecting and integrating AI frameworks, orchestrating model lifecycle management, and guiding cross-functional teams to deliver production-ready GenAI solutions. You will be the go-to expert for translating high-level business needs into robust, future-proof AI architectures.
Key Responsibilities:

AI Architecture & Solution Design:

• Architect enterprise-scale Generative AI solutions leveraging LLMs, embeddings, and retrieval-augmented generation (RAG) pipelines.
• Design and implement scalable AI microservices and APIs integrated into existing enterprise ecosystems (Azure, AWS, Google Cloud Platform).
• Lead PoCs and pilot implementations for AI-first use cases such as intelligent automation, code generation, knowledge assistants, and predictive analytics.

Innovation & Technology Leadership:

• Define Agentic AI assurance process, methodology and framework for clients based on their agentic systems
• Define and evolve the organization s AI architecture strategy, focusing on scalability, security, and ethical AI principles.
• Introduce emerging Gen AI frameworks (LangChain, LangGraph, CrewAI, OpenAI Agents SDK, etc.) to enable multi-agent orchestration and intelligent workflow automation.
• Build reusable AI accelerators, tools, and frameworks to standardize model deployment, evaluation, and governance.

Customer Engagement & Solutioning:

• Partner with clients to identify high-value AI opportunities and translate business problems into technical blueprints.
• Lead technical discussions, RFP responses, and client demos showcasing Gen AI capabilities and ROI.
• Collaborate with account leaders to shape AI roadmaps and innovation strategies for enterprise clients.

Delivery Governance & Enablement:

• Oversee architecture reviews and ensure best practices in AI model lifecycle management (training, fine-tuning, inference, observability).
• Guide engineering and data science teams in adopting AI-first design principles, model operationalization (MLOps/LLMOps), and continuous learning loops.
• Ensure compliance with data privacy, responsible AI, and enterprise governance standards.

Practice & Capability Building:

• Build and scale the Generative AI practice across North America mentoring architects, engineers, and data scientists.
• Collaborate with global CoE and platform teams to enhance reusable AI assets, domain-specific models, and evaluation frameworks.
• Evangelize AI-first engineering through thought leadership, workshops, and industry events.

Required Skills & Experience:

• 12+ years in software engineering, solution architecture, or digital transformation roles.
• 5+ years of hands-on experience in AI/ML, NLP, or Generative AI system design.
• Deep knowledge of LLMs, vector databases, and orchestration frameworks (LangChain, LangGraph, LlamaIndex, etc.).
• Strong understanding of RAG architecture, fine-tuning (LoRA/QLoRA), embeddings, and prompt engineering.
• Expertise in cloud-native AI platforms Azure OpenAI, AWS Bedrock, Vertex AI, or similar.
• Proven ability to integrate AI models into enterprise systems using APIs, microservices, and event-driven architectures.
• Excellent communication, storytelling, and client engagement skills able to translate AI concepts into business value.
• Strong leadership in cross-functional environments involving AI research, engineering, and business stakeholders.

Must Haves:
1. Extensive Agentic AI, Gen AI app testing experience with dev background
2. Good hands on experience
3. Good in communication

Preferred Qualifications:

• Prior experience leading enterprise AI transformations or building Gen AI Centers of Excellence.
• Experience implementing agentic AI systems, AI copilots, or autonomous agents in real-world business scenarios.
• Certifications in AI/ML, cloud architecture (Azure/AWS/Google Cloud Platform), or Responsible AI practices.