Artificial Intelligence Engineer - Generative AI/LLM
First seen by Alion on Oct 17, 2026.
Key Responsibilities :
- Design, develop, and deploy AI and machine learning solutions for business applications.
- Build and integrate generative AI applications using large language models (LLMs).
- Develop AI-powered workflows, intelligent automation solutions, and AI-driven applications.
- Work with frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Hugging Face.
- Develop prompt engineering strategies and optimize LLM outputs for accuracy and performance.
- Build Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases.
- Integrate AI models with APIs, databases, and enterprise applications.
- Perform data preprocessing, feature engineering, model evaluation, and performance optimization.
- Collaborate with product managers, software engineers, and data teams to translate business requirements into AI solutions.
- Monitor deployed models and troubleshoot issues related to accuracy, latency, scalability, and reliability.
- Implement best practices for responsible AI, data privacy, security, and model governance.
- Stay updated with emerging AI technologies, frameworks, and industry developments.
Required Skills & Experience :
- 3+ years of experience in AI/ML engineering, software development, or a related field.
- Strong programming skills in Python.
- Hands-on experience developing and deploying machine learning or AI-based applications.
- Understanding of machine learning algorithms, model training, evaluation, and optimization.
- Experience with generative AI and large language models (LLMs).
- Familiarity with LLM APIs and frameworks such as OpenAI, Anthropic, LangChain, or LlamaIndex.
- Experience building REST APIs and integrating AI solutions into applications.
- Knowledge of data processing, model evaluation, and AI application performance optimization.
- Understanding of databases, data pipelines, and software development best practices.
- Strong analytical, problem-solving, and communication skills.
Good to Have :
- Experience building Retrieval-Augmented Generation (RAG) applications.
- Familiarity with vector databases such as Pinecone, Weaviate, or FAISS.
- Knowledge of AI agents, multi-agent systems, and workflow orchestration.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Familiarity with Docker, Kubernetes, and CI/CD pipelines.
- Experience with MLOps, model monitoring, and production deployment.
- Knowledge of fine-tuning, embeddings, and evaluation techniques for LLMs.
Preferred Candidate Profile :
- Ability to convert business requirements into practical and scalable AI solutions.
- Strong understanding of AI system architecture and integration patterns.
- Experience working in Agile development environments.
- A continuous-learning mindset with an interest in emerging AI technologies.
Skills
Artificial Intelligence, Python, Generative AI, Machine Learning, LangChain, Tensorflow, PyTorch, LLM