We're seeking an experienced AI/ML Engineer to lead our generative AI initiatives, focusing on large language models and agentic AI. You'll design, build, and maintain end-to-end machine learning pipelines; design scalable, production-grade AI services that integrate with our internal tools, cloud platforms, and real-world data sources; and collaborate across teams to turn complex business challenges into robust, data-driven solutions.

Responsibilities:

• Design and implement effective prompt engineering and context strategies.
• Develop AI agents, including multi-agent collaboration for complex tasks.
• Implement tool-calling mechanisms and structured output generation with LLMs.
• Perform comprehensive data preprocessing and transformation for LLM-based solutions
• Apply agentic orchestration concepts for workflow automation and task breakdown.
• Integrate LLMs with external tools, including web search, data scraping, and third-party APIs.
• Develop AI-driven automated testing strategies to validate models and workflows
• Perform model selection and evaluation based on use case, performance, and cost. Conduct cost analysis for training and inference workloads across environments.
• Fine-tune large language models for task-specific performance.
• Work with cloud platforms (e.g., Azure) to deploy scalable AI systems.
• Build and maintain end-to-end ML pipelines from data ingestion to model deployment
• Design systems for both on-premise and cloud-based AI applications

Requirements:

• Minimum 4 5 years of experience in AI/ML engineering
• Strong Python programming skills
• Hands-on experience with libraries such as LangChain (or LangGraph), LlamaIndex, PyTorch, or similar
• Experience deploying and managing ML models in or On-Prem cloud environments.
• Solid understanding of ML system design, including security, scalability, and efficiency
• Understanding of LLM integrations, Context engineering, and agent-based frameworks
• Strong problem-solving skills and the ability to work on complex systems independently