Jobot
AI Architect
Base pay range: $200,000.00/yr - $240,000.00/yr
Location: Dallas or Houston, TX (hybrid work model)
This position offers a high‑visibility opportunity to influence how AI is embedded across global operations. You’ll work at the intersection of architecture, innovation, and enterprise value creation—helping to shape both near‑term solutions and long‑term strategy.
Key Responsibilities
Define and maintain architecture for GenAI, LLMs, RAG pipelines, and autonomous agent systems.
Design and implement agent orchestration workflows and agentic frameworks.
Evaluate and select AI/Agentic tools, frameworks, and platforms (e.g., LangChain, Semantic Kernel, Vertex AI, Azure OpenAI, AWS Bedrock, LangGraph, CrewAI).
Align architectural decisions with enterprise performance metrics including latency, security, cost, and explainability.
Assess emerging AI technologies and recommend adoption where appropriate.
Design scalable, modular, and observable architectures aligned with business and data strategy.
Serve as a key stakeholder in shaping the enterprise AI roadmap.
Collaborate with data architects, scientists, enterprise architecture, security, AI product managers, and business stakeholders.
Guide proof‑of‑concept development and prototype evaluations to validate architecture decisions.
Provide architecture reviews, mentorship, and feedback to AI engineering teams.
Lead structured build‑vs‑buy evaluations and influence platform roadmap decisions.
Embed responsible AI principles, privacy, and governance frameworks into AI design.
Ensure AI solutions comply with enterprise standards, security policies, and regulatory requirements.
Partner with governance, security, and compliance teams to implement transparency, monitoring, and auditability.
Qualifications
BA/BS degree or equivalent with 10+ years of relevant architecture experience.
4+ years of experience in ML or AI systems design and architecture.
Proven expertise designing and deploying enterprise‑grade GenAI, RAG models, agentic AI, and ML pipelines.
Working knowledge of interoperability protocols (e.g., Model Context Protocol, Agent‑to‑Agent communication).
Hands‑on experience with agentic frameworks (LangChain, Azure AI Agent Services, n8n, Autogen, etc.).
Familiarity with AI Gateway implementation for enforcing guardrails, monitoring, and centralized model access.
3+ years of experience building AI solutions in AWS (or equivalent cloud).
Ability to build AI POCs and design for enterprise‑scale production.
Strong collaboration and communication skills, with the ability to influence executive leadership.
Proven track record leading cross‑functional teams, including engineers and product managers.
Demonstrated ability to stay on top of emerging AI trends and best practices.
Preferred Qualifications
Understanding of MLOps and DevOps practices (CI/CD for models, observability, rollback).
Experience with CI/CD pipelines using YML, AWS CloudFormation, Terraform.
Proficiency with Kubernetes, Docker, and containerized deployment.
Strong programming skills in C#, Python, JavaScript, JSON.
Experience with Azure DevOps for recording/tracking Epics, Features, and User Stories.
Intellectual curiosity and commitment to continuous learning in AI/ML.
Equal Opportunity Employment Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories.
By applying for this job, you agree to receive calls, AI‑generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners.
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Location: Dallas or Houston, TX (hybrid work model)
This position offers a high‑visibility opportunity to influence how AI is embedded across global operations. You’ll work at the intersection of architecture, innovation, and enterprise value creation—helping to shape both near‑term solutions and long‑term strategy.
Key Responsibilities
Define and maintain architecture for GenAI, LLMs, RAG pipelines, and autonomous agent systems.
Design and implement agent orchestration workflows and agentic frameworks.
Evaluate and select AI/Agentic tools, frameworks, and platforms (e.g., LangChain, Semantic Kernel, Vertex AI, Azure OpenAI, AWS Bedrock, LangGraph, CrewAI).
Align architectural decisions with enterprise performance metrics including latency, security, cost, and explainability.
Assess emerging AI technologies and recommend adoption where appropriate.
Design scalable, modular, and observable architectures aligned with business and data strategy.
Serve as a key stakeholder in shaping the enterprise AI roadmap.
Collaborate with data architects, scientists, enterprise architecture, security, AI product managers, and business stakeholders.
Guide proof‑of‑concept development and prototype evaluations to validate architecture decisions.
Provide architecture reviews, mentorship, and feedback to AI engineering teams.
Lead structured build‑vs‑buy evaluations and influence platform roadmap decisions.
Embed responsible AI principles, privacy, and governance frameworks into AI design.
Ensure AI solutions comply with enterprise standards, security policies, and regulatory requirements.
Partner with governance, security, and compliance teams to implement transparency, monitoring, and auditability.
Qualifications
BA/BS degree or equivalent with 10+ years of relevant architecture experience.
4+ years of experience in ML or AI systems design and architecture.
Proven expertise designing and deploying enterprise‑grade GenAI, RAG models, agentic AI, and ML pipelines.
Working knowledge of interoperability protocols (e.g., Model Context Protocol, Agent‑to‑Agent communication).
Hands‑on experience with agentic frameworks (LangChain, Azure AI Agent Services, n8n, Autogen, etc.).
Familiarity with AI Gateway implementation for enforcing guardrails, monitoring, and centralized model access.
3+ years of experience building AI solutions in AWS (or equivalent cloud).
Ability to build AI POCs and design for enterprise‑scale production.
Strong collaboration and communication skills, with the ability to influence executive leadership.
Proven track record leading cross‑functional teams, including engineers and product managers.
Demonstrated ability to stay on top of emerging AI trends and best practices.
Preferred Qualifications
Understanding of MLOps and DevOps practices (CI/CD for models, observability, rollback).
Experience with CI/CD pipelines using YML, AWS CloudFormation, Terraform.
Proficiency with Kubernetes, Docker, and containerized deployment.
Strong programming skills in C#, Python, JavaScript, JSON.
Experience with Azure DevOps for recording/tracking Epics, Features, and User Stories.
Intellectual curiosity and commitment to continuous learning in AI/ML.
Equal Opportunity Employment Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, age (40 and over), disability, military status, genetic information or any other basis protected by applicable federal, state, or local laws. Jobot also prohibits harassment of applicants or employees based on any of these protected categories.
By applying for this job, you agree to receive calls, AI‑generated calls, text messages, or emails from Jobot, and/or its agents and contracted partners.
#J-18808-Ljbffr