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# AI/ML Engineer

- **Company:** Digital Links Inc
- **Location:** Minneapolis, MN, United States
- **Experience:** Expert
- **Contract:** Temporary to permanent
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, DevOps, Python (Programming Language), Machine Learning, NumPy, OpenAI, Ansible, Tensorflow, Software Engineering, SQL Databases, Systems Integration, TypeScript, Data Logging, Pinecone, Enterprise Software Applications, Pytorch, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Backend, Agentic-AI, Gitlab, Fastapi, Pandas, Kubernetes, Weaviate, Machine Learning Operations, Terraform, Jenkins
- **Published:** October 27, 2026
- **Apply:** https://www.careerjet.com/jobad/us63ba29a47765d6c8a55edd2e35c45a03

## About the Role

We are seeking a hands-on AI/ML Engineer to design, build, and deploy production-grade AI solutions. This role requires strong expertise in Generative AI, RAG (Retrieval-Augmented Generation), and enterprise integrations. The ideal candidate should be capable of independently delivering scalable AI systems aligned with business use cases.
Must-Have Skills (Non-Negotiable)

 1. Core AI/ML Engineering
Strong proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow)
Experience building and deploying end-to-end ML/AI systems
Ability to take solutions from prototype to production

 2. Generative AI & LLMs
Hands-on experience with LLMs (OpenAI, Vertex AI, etc.)
Strong prompt engineering and evaluation techniques
Experience building enterprise-grade GenAI applications

 3. RAG (Critical Requirement)
Proven experience designing and implementing RAG architectures
Experience with vector databases (Pinecone, Weaviate, etc.)
Ability to integrate domain-specific data into AI systems

 4. Agentic AI / AI Agents
Experience building AI agents / multi-agent systems
Familiarity with orchestration frameworks and modern agent SDKs

 5. API & Backend Development
Strong experience with FastAPI or Flask
Ability to build scalable AI services and APIs

 6. Cloud & Deployment (GCP Preferred)
Experience with GCP (preferred) or AWS/Azure
Deploying AI solutions in cloud-native environments
Understanding of scalability, performance, and cost optimization

 7. DevOps & Production Readiness
Experience with CI/CD (GitLab, Jenkins)
Infrastructure as Code (Terraform/Ansible)
Monitoring, logging, and AI observability
Nice-to-Have (Strong Plus)
Experience in education / digital learning platforms
Exposure to regulated environments
Knowledge of TypeScript / Java / SQL
Experience integrating AI into enterprise systems
Experience Required
5+ years in Software Engineering / AI/ML
Proven track record of:
Delivering production AI systems
Working in Agile cross-functional teams
Driving solutions with minimal oversight