AI Engineer

Home/Jobs/AI Engineer 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 Qualification Bachelor’s degree in computer science, Engineering, or related field Responsibilities 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 Additional Responsibilities 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 Nice To Have 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 More Skills 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. 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