AI ML Engineer

**AI/ML Engineer**

**Location:**

USA (Hybrid/Remote Available)

**About NCompas Technology Solutions Inc.:**

At NCompas Technology Solutions Inc., we drive business transformation through advanced AI and ML, tailored to meet unique client needs. As a Microsoft Partner, we value expertise in the Microsoft stack, but also welcome proficiency in any open source cutting-edge AI/ML platform and emerging agentic AI technologies.

**Position Summary:**

The AI/ML Engineer will design and deploy high-impact machine learning systems, working end-to-end from data collection to production-grade solutions. This high-visibility role includes building AI models, engineering advanced pipelines, and implementing agentic AI (autonomous/self-directed AI agents) for forward-thinking, customer-focused solutions.

**Key Responsibilities:**

·      
Build, deploy, and optimize robust AI and ML models utilizing prominent tools, frameworks, and cloud services (Azure ML, AWS SageMaker, GCP Vertex AI, or on-premise as needed).

·      Build efficient data pipelines for data collection, cleaning, and transformation across structured and unstructured sources.

·      Perform feature engineering using tools like Pandas, PySpark, or Databricks to ensure high-quality inputs for ML models.

·      
Engineer, productionize, and monitor agentic AI workflows, leveraging frameworks such as LangChain, LlamaIndex, OpenAI Agents, Semantic Kernel, or comparable orchestration libraries.

·      
Develop and integrate APIs or software services for AI solution delivery using languages like Python, Java, or C#.

·      
Support end-to-end data and model pipeline design, including large language models (LLMs), prompt engineering, and retrieval augmented generation (RAG) architectures.

·      
Implement best practices in MLOps, CI/CD, containerization (Docker, Kubernetes), and automated testing.

·      
Collaborate with data scientists, engineers, and customers to translate conceptual models and research into scalable, real-world systems.

·      
Stay abreast of research, experiment with new agentic and generative AI technologies, and advocate for innovative approaches aligned to business needs.

·      
Provide mentorship and participate in design/code reviews.

**Preferred:**

·      Experience with Microsoft Azure AI stack (Azure ML, Cognitive Services, Azure OpenAI Service, Synapse).

·      Familiarity with Power Platform integrations (Power Automate, Power Apps, Copilot Studio).

·      Knowledge of Azure DevOps for CI/CD and secure MLOps workflows.

**Qualifications:**

·      
Bachelor’s or Master’s in Computer Science, Engineering, or a related field.

·      
3-5 years’ experience building and deploying ML systems in cloud or on-premise environments.

·      
Proficiency in Python (preferred), and familiarity with Java, C++, or C#.

·      
Hands-on with at least one ML framework (TensorFlow, PyTorch, Keras).

·      
Experience with leading agentic AI tooling (LangChain, LlamaIndex, Semantic Kernel, OpenAI tools, AutoGen, CrewAI, etc.).

·      
Practical knowledge of integrating LLMs (OpenAI, Azure OpenAI Service, Hugging Face, etc.) into workflows.

·      
Familiarity with cloud AI/ML platforms (Azure ML, AWS SageMaker, GCP AI Platform) or strong on-premise deployment knowledge.

·      
Containerization skills (Docker, Kubernetes) and source control proficiency (Git).

·      
Understanding of software engineering fundamentals and experience with automated pipelines (MLOps).