Artificial Intelligence Engineer

We are looking for an experienced AI Engineer with 5+ years of hands-on experience in Artificial Intelligence, Machine Learning, and Applied AI.

The ideal candidate should have strong experience in designing, developing, testing, and deploying AI/ML solutions and should be comfortable taking AI initiatives from initial problem definition and POC development through production deployment.

The role requires strong technical expertise in Python, Machine Learning, Deep Learning, Generative AI, LLMs, MLOps, and cloud-native AI solutions.

Key Responsibilities

AI/ML Solution Development

• Design, develop, train, evaluate, and deploy AI/ML models for complex business problems.
• Translate business requirements into scalable AI/ML solutions.
• Develop and optimize Machine Learning and Deep Learning models.
• Apply statistical modeling and machine learning techniques to solve real-world problems.
• Work with structured and unstructured data to develop AI-driven solutions.
• Optimize models for accuracy, scalability, performance, and reliability.

POC & AI Innovation

• Develop rapid AI/ML Proofs of Concept (POCs) to validate technical feasibility and business value.
• Experiment with emerging technologies such as LLMs, Generative AI, Agentic AI, and Edge AI.
• Define appropriate evaluation metrics and success criteria for AI/ML solutions.
• Analyze POC results and recommend suitable approaches for production implementation.
• Continuously research and evaluate new AI/ML frameworks, models, and techniques.

Generative AI & LLM

• Develop and implement LLM-based and Generative AI applications.
• Work with Prompt Engineering, RAG, embeddings, vector databases, and LLM orchestration.
• Integrate LLMs with enterprise applications and APIs.
• Optimize LLM solutions for accuracy, relevance, latency, and cost.
• Experience with AI Agents / Agentic AI solutions is highly desirable.

MLOps & Production Deployment

• Work with engineering and DevOps teams to deploy AI/ML models into production.
• Implement MLOps practices for model deployment, monitoring, versioning, and lifecycle management.
• Develop scalable, highly available, and low-latency AI inference services.
• Integrate AI/ML models with APIs, microservices, and enterprise applications.
• Monitor production models and troubleshoot performance or reliability issues.
• Follow AI governance, security, compliance, and responsible AI practices.

Required Qualifications

Experience

• 5+ years of hands-on experience in AI Engineering, Data Science, Machine Learning, or Applied AI.
• Proven experience developing and deploying AI/ML solutions in production.
• Strong experience taking projects from problem definition POC development deployment.
• Strong hands-on engineering and problem-solving capabilities.