AI Backend Developer

We’re seeking AI Engineers to help design, build, and deploy next-gen AI solutions across Mercer’s global ecosystem. You will work on Generative AI, RAG pipelines, and AI agents that power internal tools, chatbots, and decision-support systems used by our consultants. This hands‑on engineering role bridges full‑stack software development and advanced AI techniques.

What You’ll Do

• Design and implement AI-driven applications, copilots, and conversational agents using LLMs (OpenAI, Anthropic, Azure OpenAI).
• Build and maintain RAG pipelines using text chunking, embeddings, and vector databases (e.g., MongoDB Atlas Vector Search, FAISS, Pinecone, Weaviate).
• Develop and optimize prompting strategies and agent reasoning logic.
• Engineer LLM‑based middleware integrations using Python and Node.js.
• Contribute to full‑stack application development using the MEAN stack (MongoDB, Express, Angular, Node.js).
• Support secure architecture by implementing MFA, OAuth flows, and containerized deployments.
• Manage CI/CD pipelines using GitHub and Jenkins, and work with containerized deployments.
• Collaborate with cross‑functional teams (data scientists, product owners, platform engineers) to bring prototypes into production.
• Maintain code quality, observability, and robustness with proper testing and documentation.

Required Qualifications

• 2+ years of experience in AI/ML or full‑stack software engineering.
• Hands‑on experience building LLM‑based applications, RAG solutions, or AI agents.
• Proficient in Python and/or Node.js and familiar with modern backend/middleware patterns.
• Solid experience in MongoDB, including vector search capabilities (Atlas Vector Search preferred).
• Experience with MEAN stack (MongoDB, Express, Angular, Node.js).
• Familiarity with prompt engineering, embeddings, and retrieval pipelines.
• Experience implementing or integrating Multi‑Factor Authentication.
• Comfortable using GitHub for source control and Jenkins for CI/CD automation.
• Excellent problem‑solving skills and the ability to communicate technical concepts.
• Strong communication skills – able to explain AI concepts to non‑technical stakeholders.

Nice to Have (But Not Required)

• Experience with Databricks, model registries, and MLOps workflows.
• Familiarity with LangChain, LlamaIndex, Dapr, or Azure AI Agent Service.
• Prior work in AI observability, testing, and platform governance.
• Understanding of cloud security, data governance, and compliance in AI systems.

Preferred Tools & Stack

• MEAN stack, Python, or any other middleware technologies.
• Databricks (Nice to have), OpenAI, Azure OpenAI
• LangChain, LlamaIndex, or similar frameworks
• Git, CI/CD, Docker, and cloud platforms (especially Azure)