AI Lead Engineer
First seen by Alion on Aug 14, 2026.
Role Summary:
We are seeking a highly experienced AI Lead Engineer to lead the design, development, and deployment of enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will be responsible for driving AI strategy, defining technical architecture, mentoring engineering teams, and delivering scalable AI-powered applications that create measurable business value.
Key Responsibilities:
AI Solution Architecture & Leadership:
- Lead the design and implementation of AI/ML and Generative AI solutions across enterprise platforms.
- Define AI architecture, engineering standards, and best practices.
- Provide technical leadership and mentorship to AI engineers, data scientists, and software developers.
- Evaluate emerging AI technologies and recommend solutions aligned with business objectives.
- Drive innovation and AI adoption across the organization.
Generative AI & LLM Development:
- Design and build applications using Large Language Models (LLMs).
- Develop enterprise solutions leveraging Azure OpenAI, OpenAI, Claude, Gemini, or similar platforms.
- Architect and implement Retrieval-Augmented Generation (RAG) solutions.
- Develop AI agents, copilots, intelligent assistants, and document processing solutions.
- Lead prompt engineering, model evaluation, fine-tuning, and optimization initiatives.
AI Engineering & MLOps:
- Build scalable AI services, APIs, and microservices.
- Implement model deployment, monitoring, observability, and MLOps pipelines.
- Develop data pipelines to support training and inference workloads.
- Optimize model performance, scalability, reliability, and cost efficiency.
- Ensure AI solutions meet security, governance, and compliance requirements.
Cloud & Platform Engineering:
- Deploy and manage AI solutions on Azure, AWS, or GCP.
- Work with vector databases, embeddings, semantic search, and knowledge management platforms.
- Leverage containerization and orchestration technologies such as Docker and Kubernetes.
- Collaborate with enterprise architecture teams to integrate AI solutions into existing systems.
Stakeholder & Delivery Management:
- Partner with business leaders and product teams to identify and prioritize AI use cases.
- Translate business requirements into technical AI solutions.
- Lead Agile delivery teams and manage project risks, dependencies, and milestones.
- Present architecture, solution designs, and implementation strategies to stakeholders.
Required Skills:
- Strong experience in Python and AI/ML solution development.
- Expertise in Generative AI, Large Language Models (LLMs), Machine Learning, Deep Learning, and NLP.
- Hands-on experience with Azure OpenAI, OpenAI APIs, LangChain, LlamaIndex, Hugging Face, Semantic Kernel, or similar frameworks.
- Strong experience in RAG, Fine-Tuning, Prompt Engineering, AI Agents, and Vector Databases.
- Knowledge of TensorFlow, PyTorch, Scikit-learn, and related AI frameworks.
- Experience in REST APIs, Microservices, Docker, Kubernetes, and CI/CD pipelines.
- Strong cloud experience with Azure, AWS, or GCP.
- Excellent leadership, communication, stakeholder management, and problem-solving skills.
Preferred Skills:
- Experience leading enterprise AI transformation programs.
- Knowledge of Responsible AI, AI Governance, Security, and Compliance frameworks.
- Experience with MLOps platforms and model lifecycle management.
- Exposure to healthcare, banking, insurance, or other regulated industries.
- AI, Cloud, or Architecture certifications are preferred.
Key Competencies:
- AI Strategy & Solution Architecture
- Technical Leadership & Mentoring
- Generative AI & LLM Expertise
- AI Agent & RAG Development
- Machine Learning & MLOps
- Cloud Architecture
- Stakeholder Management
- Innovation & Problem Solving
- Agile Delivery
- Ownership & Accountability.
Skills
Artificial Intelligence, Machine Learning, Generative AI, Data Science, Data Scientist, LLM, LangChain, MLOps, OpenAI