GenAI Solutions Architect

ANEKA TALENT SOLUTIONS CORP
Chicago, IL, United States
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Computer Vision Machine Learning Natural Language Processing Software Deployment Software Engineering Large Language Models Prompt Engineering IT Architecture Deep Learning Generative AI AI Platforms
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Virtual Agents

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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