AI Engineer

As an AI Engineer, you’ll drive the end-to-end development of advanced GenAI applications, including agentic AI agents with autonomous workflows, function calling, and LLM model fine-tuning. This role is for an experienced engineer who excels at building robust, production-grade AI systems and pushing the boundaries of what GenAI can accomplish.

Fine-tune and deploy open-source general purpose LLMs and code-generation models (e.g. Llama 4, qwen2.5) using PEFT, LoRA, QLoRA, instruction tuning, RLHF, etc..

Design GenAI applications with agentic capabilities—autonomous, goal-driven agents that can plan, reason, and execute multi-step workflows with minimal human input.

Implement function calling in workflows, enabling models to invoke external tools, APIs, databases, and services to perform actions or access real-time data.

Build agentic RAG pipelines, where LLMs coordinate data retrieval and reasoning dynamically via retrieval-augmented generation.

Create and maintain scalable pipelines, including data ingestion, labeling, feature engineering, vector DB management, and MLOps frameworks (MLflow, Kubeflow).

Containerize applications using Kubernetes and Docker.

Optimize and monitor model performance, including latency, drift, bias, privacy, and security compliance.

Collaborate cross-functionally, mediating between data, product, and engineering teams to translate requirements into agentic GenAI solutions.

Stay current with research trends like agentic RL frameworks (e.g., ARTIST), multi-agent orchestration, MCP, and secure function calling.