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Ai Engineer Architect Jobs (NOW HIRING)

PepsiCo

Senior AI Engineer, Architect

Plano, TX

Overview We are seeking a Senior AI Engineer to define and drive the end-to-end engineering of an ... Define reference architecture, design standards, and engineering guardrails for agent workflow ...

New

PepsiCo

Senior AI Engineer, Architect

Plano, TX

Overview We are seeking a Senior AI Engineer to define and drive the end-to-end engineering of an ... Define reference architecture, design standards, and engineering guardrails for agent workflow ...

New

PepsiCo

Senior AI Engineer, Architect

Plano, TX · On-site

Overview We are seeking a Senior AI Engineer to define and drive the end-to-end engineering of an ... Define reference architecture, design standards, and engineering guardrails for agent workflow ...

New

PepsiCo

Senior AI Engineer, Architect

Plano, TX · On-site

PepsiCo is seeking a Senior AI Engineer to define and drive the end-to-end engineering of an ... Responsibilities : • Technical Direction, Architecture Standards & Roadmap Ownership (30) • ...

New

NavitasPartners

Collaborate with data engineers, architects, and business teams * Ensure performance, governance, and reliability of AI systems Required Skills: * Strong experience in AI/ML and GenAI development

ClifyX

AI Architect/ AI Engineer

Mclean, VA · On-site

$64.75 - $85.25/hr

... AI architecture, standards, and governance. · Hands-on experience designing/building agent-based approaches and autonomous workflows. · Strong expertise in Prompt Engineering (Zero/Few-shot, Chain ...

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Ai Engineer Architect information

What are the key skills and qualifications needed to thrive as an AI Engineer Architect, and why are they important?

To thrive as an AI Engineer Architect, you need deep expertise in computer science, machine learning, algorithm development, and system architecture, often supported by advanced degrees and experience in AI project delivery. Familiarity with AI frameworks (such as TensorFlow or PyTorch), cloud platforms (like AWS, Azure, or GCP), and relevant certifications (e.g., Google Professional Machine Learning Engineer) is typically required. Strong communication, problem-solving, and leadership skills help you bridge technical and business requirements and guide teams effectively. These skills are crucial for designing scalable, innovative AI solutions that align with organizational goals and drive successful implementation.

How does an AI Engineer Architect typically collaborate with cross-functional teams during project development?

AI Engineer Architects regularly work alongside data scientists, software engineers, product managers, and business stakeholders to design and implement AI-driven solutions. They are responsible for translating complex business requirements into scalable AI architectures, guiding project direction, and ensuring technical feasibility. Collaboration often involves leading technical discussions, conducting code and architecture reviews, and providing mentorship to junior AI engineers. Effective communication and teamwork are essential, as AI Engineer Architects must align AI initiatives with broader organizational goals.

What are AI Engineer Architects?

AI Engineer Architects are professionals who design, develop, and oversee the implementation of artificial intelligence solutions within organizations. They combine expertise in AI technologies, such as machine learning and deep learning, with architectural skills to create scalable, robust, and efficient AI systems. Their responsibilities often include selecting appropriate AI frameworks, ensuring data pipelines are optimized, and collaborating with data scientists, engineers, and business stakeholders to align AI initiatives with organizational goals.

What is the difference between Ai Engineer Architect vs Data Scientist?

AspectAi Engineer ArchitectData Scientist
Required CredentialsBachelor's/Master's in CS, AI, or related fields; certifications in AI/MLBachelor's/Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDesigning AI architectures, developing models, integrating AI solutionsAnalyzing data, building predictive models, deriving insights
Employer & Industry UsageTech companies, AI-focused firms, R&D departmentsFinance, healthcare, marketing, tech firms

While both roles require expertise in AI and machine learning, Ai Engineer Architects focus on designing and implementing AI systems and architectures, whereas Data Scientists analyze data to generate insights and build models. The roles often overlap but differ mainly in scope and responsibilities.

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Ai Engineer Architect jobs near you

AI Engineer/ Architect

Purple Drive Technologies

Bloomfield, CT • On-site

Full-time

Posted 16 hours ago

Job description

Overview:
Job Title: AI Engineer/ Architect
The ideal candidate will have a deep understanding of Gen AI and Large Language Models and the ability to design, develop and deploy Gen AI solutions that address business problems. They will have excellent programming skills and be proficient in at least one of the major programming languages used in AI such as Python
Responsibilities:
  • Strong knowledge and previous experience on building ML/ NLP models, textual data
  • Strong knowledge on LangChain, LlamaIndex, Vector databases like Redis, Chroma & Pinecone.
  • Good knowledge on Gen AI monitoring tools like W&B / LangSmith.
  • Develop scalable and efficient Gen AI solutions that can be deployed in production environments.
  • Good knowledge on CICD, deployment process ( OpenShift is preferred and desirable)
  • Strong knowledge on evaluating Gen AI output
  • Strong knowledge on fine tuning LLMs
  • Evaluate and improve existing Gen AI solutions to ensure optimal performance and accuracy
  • Develop and implement best practices for Gen AI applications and Gen AI patterns.
  • Conduct experiments and analyses to evaluate the performance of Gen AI solutions.
  • Develop and maintain documentation for Gen AI-based solutions
  • Familiarity with cloud computing platforms such as AWS Bedrock, Azure or Google Cloud Vertex AI.
  • Mainly perform as Individual contributor, however collaborate with data scientists and other AI professionals to augment digital transformation efforts by piloting and then deploying use cases to production.

Soft Skills:
  • Open to work in a agile and flexible environment - attitude to quickly switch on/off to different projects within the team
  • Effectively communicate thoughts, insights and plans to cross-functional teams. Should have ability to explain complex technical concepts to non-technical stakeholders like business unit executives.
  • Excellent presentation skills to engage with business users to gain an in-depth understanding of priorities and needs.
  • Provide expert advice to determine options and solutions to project issues and challenges to ensure optimal service delivery and client satisfaction.

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