About the role:
We are seeking a Python Backend Engineer to build and maintain AI-powered backend services across the Sitecore platform. You will work with LLM integrations, agentic workflows, RAG pipelines, and contribute to production‑grade generative AI systems that power intelligent digital experiences. You will operate in an AI-driven environment, leveraging copilots and intelligent agents to accelerate development and workflows.
Key Responsibilities:
- Develop and productionize LLM pipelines, including retrieval, orchestration, prompt strategies, and semantic processing.
- Implement and maintain RAG pipelines, embeddings generation, and vector search capabilities.
- Build resilient backend services and APIs supporting AI-driven platform features in a multitenant environment.
- Contribute to evaluation frameworks measuring accuracy, relevance, and trustworthiness of AI outputs.
- Leverage copilots and intelligent agents to automate workflows, code tasks, and operational processes.
- Work with agentic frameworks (e.g., LangChain, LangGraph, AI Foundry, or similar) to design and execute multi-step AI workflows.
- Contribute to backend capabilities that integrate with MCP-based tooling and structured AI action frameworks.
- Ensure system scalability, cloud-native robustness, and adherence to engineering best practices.
Qualifications
Preferred Skills and Experience:
- 2+ years of professional software engineering experience.
- Strong experience developing backend systems using Python.
- Hands-on experience building generative AI applications using LLMs.
- Experience with RAG, embeddings, vector stores, and semantic retrieval.
- Familiarity with evaluation techniques for LLM outputs.
- Experience with FastAPI, Flask, Pydantic, or related frameworks.
- Experience with Azure, Docker, Kubernetes, and CI/CD pipelines.
- Familiarity with relational and non-relational databases.
- Understanding of agentic systems and orchestration patterns.
- Awareness of working with multitenant AI platforms and isolated tenant workloads.
Nice to Have:
- Experience with knowledge graphs, ontologies, or taxonomy-driven retrieval.
- Experience with fine‑tuning or optimizing LLMs.
- Awareness of AI safety, responsible AI practices, or safety guardrail implementation.
- Experience building solutions on Azure or AWS.
- Background in contextual help, AI assistants, or automation-focused AI solutions.
Additional Information
We champion flexibility and hybrid work options to support varying lifestyles and personal needs. At the same time, we value the power of in-person collaboration to build community, spark innovation, and strengthen connections. Our approach ensures you can work in ways that suit you best while still engaging with colleagues to share ideas and grow together. #LI-Hybrid #LI-DNP