AI Engineer

Job Summary

We are looking for a highly skilled Lead AI Engineer with deep expertise in Generative AI, Agentic AI, Machine Learning, and Data Science to lead the development of next-generation AI solutions. The ideal candidate will drive AI strategy, architect scalable AI platforms, mentor engineering teams, and deliver enterprise-grade AI applications that create measurable business impact.

This role requires strong hands-on experience in building LLM-powered applications, AI Agents, RAG solutions, predictive analytics models, and advanced machine learning systems while leading cross-functional teams in a fast-paced environment.

Roles and Responsibilities

AI & GenAI Leadership

• Lead the design, development, and deployment of enterprise AI and Generative AI solutions.
• Define AI architecture, technology strategy, and best practices across projects.
• Build scalable GenAI platforms leveraging LLMs and Agentic AI frameworks.
• Drive innovation by evaluating emerging AI technologies and industry trends.
• Collaborate with executive leadership to identify AI-driven business opportunities.

Generative AI & Agentic AI

• Design and develop applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral.
• Architect and implement Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge management.
• Develop and deploy Autonomous AI Agents and Multi-Agent Systems using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, and LangChain.

Machine Learning & Data Science

• Lead the development of predictive, classification, recommendation, forecasting, and anomaly detection models.
• Apply advanced statistical methods and machine learning techniques to solve complex business problems.
• Design end-to-end ML pipelines from data ingestion to model deployment and monitoring.
• Work closely with Data Science teams to operationalize AI/ML models in production.
• Drive model performance optimization and continuous improvement.

MLOps & Deployment

• Establish MLOps and LLMOps frameworks for scalable production deployments.
• Develop CI/CD pipelines for AI and ML applications.
• Implement model monitoring, drift detection, governance, and performance tracking.
• Ensure security, reliability, scalability, and compliance of AI platforms.

Leadership & Stakeholder Management

• Lead and mentor AI Engineers, Machine Learning Engineers, and Data Scientists.
• Conduct architecture reviews and provide technical guidance.
• Collaborate with business stakeholders to translate requirements into AI solutions.
• Drive project planning, estimation, delivery, and stakeholder communication.
• Foster innovation and knowledge-sharing within the AI organization.

Required Skills and Qualifications

Generative AI & Agentic AI

• Strong experience with:
• Large Language Models (GPT, Claude, Gemini, Llama, Mistral)
• RAG Architectures
• AI Agents and Multi-Agent Systems
• Prompt Engineering
• Fine-Tuning and Model Optimization
• Knowledge Graph Integration
• Expertise in:
• LangChain
• LangGraph
• AutoGen

Machine Learning & Data Science

• Strong foundation in:
• Supervised and Unsupervised Learning
• Deep Learning
• NLP
• Experience with:
• Scikit-learn
• TensorFlow
• PyTorch
• XGBoost
• LightGBM

Programming

• Expert-level proficiency in Python.
• Strong coding and software engineering practices.
• Experience in API development and microservices architecture.
• Google Vertex AI
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related discipline.
• 10+ years of experience in Software Engineering, Data Science, AI/ML, or Data Engineering.
• 5+ years of hands-on Machine Learning and Data Science experience.
• 2+ years of experience in Generative AI and LLM-based solution development.
• Proven experience leading AI teams and enterprise-scale AI implementations.

Preferred Qualifications

• Experience building production-grade AI Agents and autonomous workflows.
• Experience implementing Responsible AI and AI Governance frameworks.
• AI certifications from Microsoft, Google, AWS, or equivalent.