The Forward Deployed Engineer (FDE) build team turns the enterprise’s highest-value AI opportunities into production reality, partnering with US-based FDEs to deliver solutions across lines of business. As an Engineer, you will build and deliver production-grade AI agents and solutions – leveraging LLM APIs, agentic workflows, and Retrieval-Augmented Generation (RAG) – that drive employee productivity, process optimization, and smarter decision-making. Working hands-on within established patterns and reference implementations, and collaborating closely with senior engineers, FDEs, and cross-functional teams, you will ensure AI-driven solutions are effectively integrated into enterprise workflows.
Responsibilities:
- Build and deliver RAG pipelines, agentic workflows, and multi-model orchestration components for high-value use cases, following established patterns and reference implementations
- Develop APIs, services, and integration components that connect AI capabilities to enterprise data and systems
- Apply prompt engineering and evaluation techniques to optimize AI system performance, accuracy, and reliability
- Partner with FDEs and senior engineers to turn prioritized opportunities into working, production-ready solutions
- Monitor, test, and continuously improve AI systems for scalability, reliability, and measurable impact
- Contribute to CI/CD workflows and engineering best practices for quality and maintainability
- Collaborate with cross-functional teams to integrate AI solutions into enterprise workflows
- Build and maintain key artifacts, including design notes, test scripts, and documentation
Requirements
- 5+ years of hands-on experience building AI solutions using LLMs – prompt engineering, RAG, or agentic workflows
- Experience working in agile development cycles to support rapid, effective delivery
- Strong problem-solving skills and a drive to apply creative solutions in AI agent development
- Clear communication skills for effective collaboration with FDEs and cross-functional teams
- Experience with LLM APIs, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex)
- Experience developing APIs and integration components
- Experience with cloud platforms (AWS/Azure/GCP)
- Hands-on experience with prompt and context engineering, fine-tuning, and agentic workflows
- Working knowledge of designing retrieval-augmented generation (RAG) pipelines
- Experience with LLM APIs, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex)
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