As an Engineer, AI, 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.

We pride ourselves on encouraging a culture of innovation, agile ways of working, and transparency in all we do. Join us in embodying the spirit of the Un-carrier and make a tangible impact!

What You'll Do :

- 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.

What You'll Bring :

- Bachelor's degree in Computer Science, Engineering, or related field, plus 3+ years of related work experience; or advanced degree with 1 year; or equivalent combination of education and experience.

- 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).

- Experience developing APIs and integrating AI capabilities into enterprise applications.

- 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.

Must Have Skills :

- 5+ years hands-on experience building AI solutions using LLMs - prompt engineering, RAG, or agentic workflows.

- 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).

Nice-to-Have :

- Experience with agent and tool-use frameworks, including connector patterns (e.g., MCP).

- Experience with LLM evaluation frameworks and AI observability.

- Familiarity with frontend technologies (e.g., React) for building end-user AI experiences.

- Experience with CI/CD practices and agile tools (JIRA, Confluence).

- Relevant AI/ML or cloud certifications.

- Experience working in a forward-deployed, consulting, or customer-facing engineering model.