Position : Lead Engineer AI/ML

Employment Type : Full-Time (Internal Position)

Experience Required : 8 to 12 Years

Qualification :

- Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, or a related field.

Notice Period : Immediate to 15 Days Preferred

Mode of Work :

Work From Office (5 Days a Week)

Interview Process :

Round 1 : Technical Interview

Round 2 : Technical Interview (Face-to-Face)

Round 3 : Techno-Managerial Interview (Face-to-Face)

Round 4 : Techno-Managerial & HR Interview

Role Description :

We are seeking a highly skilled Lead Engineer AI/ML to lead the design, development, and deployment of enterprise-grade Artificial Intelligence and Machine Learning solutions, with a strong focus on Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI architectures. This role requires hands-on expertise in delivering end-to-end GenAI solutions, from proof of concept to production deployment, while driving innovation and technical excellence across AI initiatives.

Key Responsibilities :

- Design, develop, and deliver scalable AI/ML and Generative AI solutions aligned with business objectives.

- Lead the implementation of GenAI use cases, including RAG-based chatbots, intelligent automation, domain-specific AI models, and AI-powered assistants.

- Develop and optimize LLMs, prompt-driven AI agents, and agentic workflows for enterprise applications.

- Build Proof of Concepts (PoCs), blueprints, and production-ready AI solutions to validate business requirements.

- Develop and deploy machine learning models using Python, TensorFlow, Scikit-learn, or equivalent ML frameworks.

- Design AI architectures leveraging embeddings, vector databases, semantic search, and knowledge retrieval systems.

- Deploy, monitor, and maintain AI models using modern MLOps practices, including CI/CD pipelines and model lifecycle management.

- Utilize cloud-native AI services on Microsoft Azure, AWS, or Google Cloud Platform (GCP) for scalable AI deployments.

- Evaluate emerging AI technologies, frameworks, and cloud AI services to recommend best-fit solutions.

- Collaborate with business stakeholders, product teams, and engineering teams to define AI roadmaps and deliver impactful AI initiatives.

- Establish AI/ML engineering best practices, coding standards, and architecture guidelines across projects.

- Ensure responsible AI implementation by incorporating enterprise security, governance, compliance, and ethical AI principles throughout the development lifecycle.

Must-Have Skills :

- Strong hands-on experience with Python, Machine Learning, Generative AI, and Large Language Models (LLMs).

- Proven experience delivering production-grade Generative AI projects.

- Practical experience building RAG-based applications, AI automation workflows, and domain-specific AI solutions.

- Strong understanding of AI architecture, embeddings, vector databases, and semantic search.

- Experience with LLM fine-tuning, prompt engineering, and agentic AI frameworks.

- Hands-on experience with model deployment, monitoring, and CI/CD pipelines.

- Working knowledge of cloud AI platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).

- Strong analytical, problem-solving, and technical leadership skills.

Good-to-Have Skills :

- Experience with TensorFlow, Scikit-learn, or other advanced machine learning frameworks.

- Exposure to MLOps platforms and AI model lifecycle management.

- Experience implementing enterprise AI governance and Responsible AI practices.

- Knowledge of AI security, compliance, and data privacy standards.

- Experience mentoring engineering teams and leading AI solution delivery in enterprise environments.