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