AI Data Engineer
First seen by Alion on Sep 8, 2026.
AI Engineer
Position Summary :
We are seeking an innovative AI Engineer to design, develop, test, and deploy AI-powered solutions that drive business value through automation, advanced analytics, and intelligent applications.
The AI Engineer will collaborate with cross-functional teams to build and test scalable machine learning and generative AI solutions that enhance operational efficiency and improve customer experiences.
Key Responsibilities :
- Design, develop, test, and deploy AI/ML and Generative AI solutions to solve complex business problems.
- Build and optimize data pipelines to support AI model training and inference.
- Develop and integrate Large Language Model (LLM) applications, AI agents, and Retrieval-Augmented Generation (RAG) solutions.
- Create scalable APIs and AI services for enterprise applications.
- Test agentic solutions and validate outputs to ensure accuracy, reliability, and expected behavior.
- Collaborate with data engineers, software developers, and business stakeholders to translate requirements into AI solutions.
- Evaluate, fine-tune, and monitor AI models for accuracy, performance, and reliability.
- Implement MLOps best practices for model deployment, testing, monitoring, and lifecycle management.
- Ensure AI solutions comply with enterprise security, governance, and responsible AI standards.
- Stay current with emerging AI technologies and recommend innovative approaches.
Required Qualifications :
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Strong programming skills in Python and SQL.
- Experience with Large Language Models (OpenAI, Anthropic, Llama, etc.) and prompt engineering.
- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with REST APIs, Git, and software development best practices.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications :
- Experience with Snowflake, Databricks, or modern data platforms.
- Knowledge of vector databases, semantic search, and RAG architectures.
- Experience with AI orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.
- Familiarity with Docker, Kubernetes, and CI/CD pipelines.
- Experience developing AI-powered analytics dashboards using Streamlit.
Success Measures :
- Deliver scalable AI solutions that improve business outcomes.
- Automate manual processes through AI-driven workflows.
- Improve model accuracy, performance, and reliability.
- Successfully test agentic workflows and validate outputs against expected results.
- Partner effectively with stakeholders to translate business needs into AI capabilities.
- Continuously evaluate and adopt emerging AI technologies to drive innovation.
Skills
Python, Data Engineering, SQL, Data Management, ETL, RAG, LLM, Generative AI