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AI Engineer
Hollstadt Consulting
Minnesota
3 years
Today
$126.5K–168.7K/yr
Full-time
Remote
Skills Required
LLM
RAG
Gen AI
Agentic AI
OpenAI
Azure OpenAI
Gemini
Anthropic
Prompt Engineering
Machine Learning
AI
AWS
Amazon Bedrock
AWS Textract
MCP
Description
AI Engineer role within Hollstadt Consulting’s AI Center of Excellence, focused on building AI, GenAI, and Agentic AI solutions for business workflows and user experience improvements.
Company: Hollstadt Consulting
Role: AI Engineer
Location: Remote - local preferred but not required
Experience
Deep learning, Cloud AI technologies, Azure, GCP, Responsible AI, ML Ops, CI/CD for ML, Model monitoring, Versioning, Python, Context Engineering, Google A2A, REST APIs, Intelligent Document Processing, OCR, AWS Lambda, Bedrock, Step Functions, API Gateway, IAM, AWS Sagemaker, ECS, S3, TensorFlow, PyTorch, scikit-learn, SQL, Feature engineering, Docker, Airflow, Kubeflow, Git, Jira, Confluence, Dynatrace, O365, PDFs, webpages, SalesForce, Oracle, Snowflake, MS Copilot
Prepare for this role
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AI Engineer
Hollstadt Consulting
Minnesota
3 years
Today
$126.5K–168.7K/yr
Full-time
Remote
Skills Required
LLM
RAG
Gen AI
Agentic AI
OpenAI
Azure OpenAI
Gemini
Anthropic
Prompt Engineering
Machine Learning
AI
AWS
Amazon Bedrock
AWS Textract
MCP
Description
AI Engineer role within Hollstadt Consulting’s AI Center of Excellence, focused on building AI, GenAI, and Agentic AI solutions for business workflows and user experience improvements.
Company: Hollstadt Consulting
Role: AI Engineer
Location: Remote - local preferred but not required
Experience
- 3 years of experience designing and deploying ML/AI solutions in real-world environments
- Very strong Python skills
- Strong hands-on experience with LLM APIs using Python and Python-based frameworks
- Strong hands-on experience in prompt engineering, context construction, and grounding strategies
- Strong hands-on experience with Retrieval Augmented Generation, including extracting, chunking, and creating embeddings from unstructured documents
- Comfortable building Model Context Protocol clients, servers, and hosts
- Strong expertise in building REST APIs and integrating with internal and external APIs
- Hands-on experience with Intelligent Document Processing and/or OCR technologies on complex documents
- Deep experience in AWS
- Strong experience with observability tools like Dynatrace or similar GenAI observability tools
- Proficiency in Python and common ML/AI libraries
- Strong understanding of data engineering, SQL, and feature engineering
- Hands-on experience with cloud services such as AWS Sagemaker, Lambda, ECS, S3, and IAM
- Familiarity with containerization and orchestration
- Working with version control and collaboration tools
- Bachelor’s degree in computer science, Engineering, or related field
- Support the AI Center of Excellence across cross-functional teams
- Design, develop, and deploy machine learning, artificial intelligence, GenAI, and Agentic AI solutions
- Address domain-specific needs
- Improve user experiences
- Automate business workflows
- Work across GenAI platforms and third-party GenAI platforms and libraries
- Automate extraction of complex multimodal unstructured content into accurate structured content
- Design and build MCP hosts, clients, and servers
- Establish frameworks for automated LLM testing
- Create regression test suites to detect drift or prompt breakage
- Integrate with internal and external web services using secure authentication and authorization
- Adopt safe practices against prompt injections and jailbreaks
- Design, develop, and deploy production-grade traditional ML models
- Design, maintain, and optimize end-to-end AI/ML pipelines on cloud infrastructure
- Ensure AI/ML solutions are scalable, reliable, secure, and cost-effective
- Create reusable components, frameworks, and best practices to accelerate AI development
- Design and develop GenAI solutions using prompt engineering, Context Engineering, RAG, and custom pipelines
- Design and develop interoperable AI agents using MCP and/or Google A2A
- Partner with data scientists, architects, product managers, business stakeholders, and technical teams
- Provide hands-on technical support and mentorship to technical teams across the enterprise
- Support secure enterprise deployment aligned with enterprise security guidelines
- Ensure AI/ML solutions conform to enterprise data privacy, AI governance, and observability expectations
- Translate ambiguous business problems into clear technical ML/AI tasks
- Communicate complex ideas clearly to technical and non-technical stakeholders
- Learn and adapt quickly to emerging AI technologies, techniques, and tools
- Design and develop ML/AI solutions in cloud-native environments
- Master’s in a related technical field
- Hands-on experience with agentic AI frameworks
- Prior contributions to open-source AI/ML projects or published research
- AI/ML certifications from cloud providers
- Experience in highly regulated industries such as healthcare or finance
Deep learning, Cloud AI technologies, Azure, GCP, Responsible AI, ML Ops, CI/CD for ML, Model monitoring, Versioning, Python, Context Engineering, Google A2A, REST APIs, Intelligent Document Processing, OCR, AWS Lambda, Bedrock, Step Functions, API Gateway, IAM, AWS Sagemaker, ECS, S3, TensorFlow, PyTorch, scikit-learn, SQL, Feature engineering, Docker, Airflow, Kubeflow, Git, Jira, Confluence, Dynatrace, O365, PDFs, webpages, SalesForce, Oracle, Snowflake, MS Copilot
Prepare for this role
Recommended resources to build the skills for this position. Sponsored.
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Zenaique
Curated AI agent interview questions from Zenaique.
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An extended AI agent interview question set from Zenaique.
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A shorter RAG interview prep set for quick review.
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Salary : $126,500 - $168,700