Software Engineering, AI/ML, Retail and Marcom Engineering

What you'll do

• Drive the end-to-end machine learning project lifecycle from initial conception to production deployment.
• Design, build, and optimize production systems involving GenAI, LLMs, Graph RAG, and multi-modal models.
• Engineer intelligent conversational and agentic workflows to redefine customer brand experiences.
• Develop robust pipelines and applications that leverage LLM technologies to unlock actionable insights at scale.
• Establish engineering best practices for LLM, RAG, and conversational AI implementations to ensure high performance.
• Build and deploy advanced AIOps solutions for clustering, classification, anomaly detection, and capacity prediction.
• Integrate AI and bot systems with backend systems, databases, and APIs to deliver end-to-end solutions.
• Implement LLMOps practices including production evaluation, guardrails, observability, and cost and latency optimization.

What we're looking for

• BS or MS in Engineering, Computer Science, or a related field, or equivalent practical experience.
• 5 years of hands-on experience implementing AI/ML models in enterprise systems.
• Knowledge of core AI/ML concepts including supervised/unsupervised learning, deep learning, and anomaly detection.
• Expertise in NLP, NLU, and Conversational AI, including designing and deploying bots with intent recognition and dialogue management.
• Experience taking GenAI solutions (LLMs and RAG) into production with a solid understanding of LLM architectures.
• Mastery of Python and key AI/ML libraries and frameworks such as Pandas, NumPy, TensorFlow, and PyTorch.
• Ability to integrate AI and bot systems with backend systems, databases, and APIs to deliver end-to-end solutions.
• Troubleshooting and analytical skills for diagnosing complex issues in distributed environments.