GenAI Solutions Architect
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Role details
Tech stack
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Job description
We are seeking a highly technical GenAI Solutions Architect to join a growing AI Center of Excellence (CoE) focused on delivering enterprise-scale Generative AI solutions. This individual will be responsible for designing, prototyping, and evangelizing innovative AI architectures that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and advanced machine learning technologies.
The ideal candidate has a strong foundation in Machine Learning, Natural Language Processing (NLP), and/or Computer Vision, and has evolved into a solution architecture role where they work directly with business stakeholders to identify opportunities, build proof-of-concepts (POCs), secure funding, and transition successful solutions to engineering teams for production deployment.
Responsibilities
-
Design and architect enterprise Generative AI solutions leveraging LLMs, RAG frameworks, and Agentic AI architectures.
- Partner with business leaders and technical stakeholders to identify high-value AI use cases and translate requirements into scalable solution designs.
- Build and demonstrate AI proof-of-concepts (POCs), MVPs, and prototypes to validate business value and technical feasibility.
- Lead solutioning efforts within an AI Center of Excellence (CoE) environment, evaluating emerging technologies and recommending best-fit architectures.
- Define end-to-end AI architecture including model selection, orchestration, vector databases, prompt engineering strategies, and deployment patterns.
- Work closely with engineering teams to transition approved solutions into production environments.
- Create technical presentations, architecture diagrams, and executive-level communications for both technical and non-technical audiences.
- Evaluate and recommend AI platforms, frameworks, and tooling based on business objectives and technical requirements.
- Stay current on emerging trends within Generative AI, Agentic AI, multimodal AI, and machine learning ecosystems.
Requirements
8+ Years
Visa
, and EAD
Interview Process
1-2 rounds
Communication
Excellent Communication Skills - MUST HAVE
Background
Data Science / Machine Learning - MUST HAVE, * MUST HAVE DATA SCIENCE/ML BACKGROUND
- 8+ years of experience in Software Engineering, Machine Learning, AI, or Solution Architecture roles.
- Strong technical background in Machine Learning, NLP, Computer Vision, or related AI disciplines.
- Hands-on experience architecting Generative AI solutions in enterprise environments.
- Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
- Experience with Agentic AI frameworks and autonomous workflow orchestration.
- Deep understanding of Large Language Models (LLMs) and prompt engineering methodologies.
- Experience working within an AI Center of Excellence (CoE) or similar innovation-focused organization.
- Proven track record of building successful AI POCs and advancing them to funded initiatives and production implementations.
- Excellent communication, presentation, and stakeholder management skills.
Technical Requirements
Experience with several of the following technologies:
- Large Language Models (OpenAI, Claude, Gemini, Llama, etc.)
- RAG Architecture
- Agentic AI Frameworks
-
Vector Databases:
- Pinecone
- Weaviate
- Chroma
- FAISS
Google Vertex AI, * Experience leading enterprise AI transformation initiatives.
- Experience evaluating and selecting GenAI technologies for large organizations.
- Background working across multiple AI domains including NLP, Computer Vision, and Predictive Analytics.
- Experience estimating ROI and business value for AI investments.
- Experience presenting AI strategy and architecture recommendations to executive leadership.
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