Generative AI Engineer

Role overview

Responsibilities

• check_circle Design and implement generative AI solutions (RAG, automation, agentic workflows)
• check_circle Translate product requirements and use cases into scalable technical architectures
• check_circle Build and optimize prompt strategies, LLM workflows, and agent-based systems
• check_circle Develop Retrieval-Augmented Generation (RAG) pipelines using enterprise data
• check_circle Integrate LLMs into applications via APIs and microservices
• check_circle Collaborate with product and delivery leads to iterate on features and solutions
• check_circle Evaluate and improve model performance (accuracy, latency, cost, reliability)
• check_circle Implement logging, monitoring, and guardrails for AI systems
• check_circle Rapidly prototype and test new AI capabilities
• check_circle Leverage AI tools to accelerate development, debugging, and experimentation

Basic qualifications

• 3–6+ years of software engineering experience
• Strong programming skills (Python preferred)
• Hands-on experience working with LLMs (e.g., OpenAI, Claude, open-source models)
• Experience building APIs and working with backend systems
• Familiarity with data pipelines, system integration, and cloud environments
• Understanding of how AI/ML systems work (not just usage, but implementation)

Preferred qualifications

• Experience with RAG architectures and vector databases
• Familiarity with frameworks (LangChain, LlamaIndex, etc.)
• Experience with agentic workflows or tool-using LLM systems
• Exposure to fine-tuning or deploying open-source models
• Experience in enterprise-scale environments

Benefits

• check_circle Pay: From $65.00 per hour