7 days ago

Gen AI Architect

Qualitest

On Site
Full Time
$155,000
California, United States

Job Overview

Job TitleGen AI Architect
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$155,000
LocationCalifornia, United States

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Job Description

About Qualitest and the Gen AI Architect Role

Are you interested in working with the World’s leading AI-powered Quality Engineering Company? Ready to advance your career, team up with global thought leaders across industries and make a difference every day? Join us at Qualitest!

We are looking for a Gen AI Architect to join our growing team in US, (Remote or Bay Area).

This role requires 12+ years overall experience in technology and digital engineering, with 5+ years of hands-on experience in AI/ML, and at least 3+ years in Agentic AI, Generative AI (LLMs, RAG, multimodal, agentic systems).

Role Overview

The Gen AI Architect – North America will 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, GCP).
  • 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.

Top 3 Must Haves

  • Extensive Agentic AI, Gen AI app testing experience with dev background.
  • Good hands on experience.
  • 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/GCP), or Responsible AI practices.

Key skills/competency

  • Generative AI
  • LLMs
  • RAG Architecture
  • Agentic AI
  • Cloud AI Platforms (Azure/AWS/GCP)
  • Enterprise Architecture
  • MLOps/LLMOps
  • LangChain/LangGraph
  • Vector Databases
  • API/Microservices Integration

Tags:

Gen AI Architect
Generative AI
LLMs
RAG
Agentic AI
AI/ML
Enterprise Architecture
Cloud AI
MLOps
LangChain
Vector Databases
Software Engineering
Solution Design
NLP
API Integration
AWS
Azure
GCP
Fine-tuning
Prompt Engineering
Microservices

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How to Get Hired at Qualitest

  • Research Qualitest's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume: Highlight your 12+ years of experience, particularly in Gen AI architecture, LLMs, RAG, and cloud AI platforms for the Gen AI Architect role.
  • Showcase your portfolio: Prepare examples of enterprise-scale AI solutions, agentic systems, or significant AI transformation projects you've led.
  • Master technical concepts: Deeply understand LLM architectures, RAG, MLOps/LLMOps, and leading frameworks like LangChain, as expected for a Qualitest Gen AI Architect.
  • Practice client engagement: Be ready to articulate business value from complex AI concepts and discuss ethical AI principles with confidence.

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