Artificial Intelligence Engineer

JD:

Were looking for an AI Developer to design, build, and ship production-grade AI-powered features and systems. Youll work with LLMs, retrieval pipelines, and agentic workflows, turning prototypes into reliable, scalable products used by real customers.

Key Responsibilities

• Design and build LLM-powered applications, including RAG pipelines, tool-calling agents, and multi-step workflows
• Integrate foundation model APIs (Anthropic, OpenAI, Azure OpenAI, open-source models) into backend services
• Develop prompt strategies, evaluation harnesses, and guardrails to improve output quality, safety, and consistency
• Build and maintain data pipelines for embeddings, vector search, and knowledge ingestion
• Monitor and optimize latency, cost, and reliability of AI systems in production
• Collaborate with product, design, and platform teams to translate business problems into AI solutions
• Write clean, tested, well-documented code and participate in code and design reviews
• Stay current with advances in the AI ecosystem and evaluate new tools and techniques

Required Qualifications

• 3+ years of software development experience, with at least 1 year building LLM or ML-based applications
• Strong proficiency in Python (or TypeScript/C#) and REST/async API design
• Hands-on experience with LLM APIs, prompt engineering, and function/tool calling
• Experience with vector databases and embeddings (e.g., Azure AI Search, Pinecone, pgvector, Qdrant)
• Familiarity with cloud platforms (Azure) and containerized deployment (Docker, Kubernetes)
• Solid understanding of software engineering fundamentals: testing, CI/CD, version control, observability
• Ability to communicate technical trade-offs clearly to both technical and non-technical stakeholders

Preferred Qualifications

• Experience with agent frameworks (LangChain, LangGraph, Semantic Kernel, AutoGen, MCP)
• Experience building LLM evaluation pipelines and automated regression testing
• Knowledge of fine-tuning, model distillation, or running open-source models
• Understanding of security, privacy, and compliance considerations for AI systems (PII handling, prompt injection, tenant isolation)
• Experience in multi-tenant SaaS or enterprise environments
• Background in data engineering or MLOps