Senior AI Engineer - RAG/LLM
First seen by Alion on Aug 24, 2026.
Job Summary :
We are looking for a Senior GenAI / AI Engineer with strong hands-on experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Machine Learning and Deep Learning. The role involves designing, developing, integrating, deploying and scaling production-ready AI/ML solutions, including RAG applications, AI chatbots and AI agents.
The candidate will work closely with data, infrastructure and business/client stakeholders to translate requirements into scalable AI solutions and take them from development through production, evaluation and monitoring.
Key Responsibilities :
- Build and scale Generative AI solutions using LLMs, RAG and AI Agents.
- Develop AI/ML solutions using Machine Learning and Deep Learning.
- Build and deploy RAG-based applications and AI chatbots.
- Train, fine-tune and optimize AI/ML models.
- Productionize ML/AI pipelines and Python services.
- Integrate AI solutions with business applications and APIs.
- Work with data teams on datasets, SQL and ETL.
- Implement AI/ML solutions across AWS, GCP and/or Azure.
- Apply MLOps practices including CI/CD, Docker, Kubernetes and MLflow.
- Monitor and evaluate model and RAG performance and improve accuracy.
- Apply Responsible AI principles, including appropriate handling of PII and model risks.
- Understand business and technical requirements and convert them into solution designs.
- Partner with data, infrastructure and business/client stakeholders to deliver scalable AI solutions.
Required Skills & Experience :
- 8 - 12 years of overall IT experience.
- 5+ years of hands-on AI/ML development experience.
- Advanced Python programming.
- Strong experience with LLMs and Generative AI.
- Hands-on experience with RAG and embedding models.
- Understanding and practical experience with AI Agents / Agentic AI.
- Strong knowledge of Machine Learning and Deep Learning.
- Experience with model training, fine-tuning and optimization.
- Strong understanding of model evaluation and performance monitoring.
- Experience with SQL, ETL and data engineering.
- Experience integrating AI solutions through APIs and business applications.
- Experience with AWS, GCP or Azure.
- Experience with MLOps, CI/CD, Docker, Kubernetes and/or MLflow.
- Strong statistical, analytical and problem-solving skills.
- Understanding of Responsible AI, PII and AI model risks.
- Strong requirement elicitation, analysis and solution-design capabilities.
- Good communication and stakeholder-management skills.
Skills
Machine Learning, Generative AI, LLM, RAG, Python, Agentic AI, MLOps, Artificial Intelligence