AI Lead Engineer

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.

(ref:hirist.tech)