Job Overview
Lead design and delivery of production-grade AI features for our customer facing product finder tool askchemille.com. Architect RAG pipelines, optimize prompts, and ensure security, observability, and cost efficiency. Drive integration with Snowflake, SAP, SharePoint, and PostgreSQL while mentoring junior engineers.
Responsibilities
- Own end-to-end delivery of AI-powered features and APIs.
- Architect and optimize RAG pipelines using Azure AI Search and embeddings.
- Integrate enterprise data sources (Snowflake, SAP, SharePoint, PostgreSQL) securely and efficiently.
- Implement guardrails, safety checks, and compliance measures.
- Establish CI/CD pipelines, observability dashboards, and cost monitoring.
- Mentor junior engineers and lead technical design reviews.
- Provide input on AI solution architecture.
- Integrate and operationalize Azure AI modelbased applications, including Agentic Ai, LLMs, Embeddings, and RetrievalAugmented Generation (RAG) solutions.
- Develop, deploy and maintain productiongrade Agentic Ai systems & LLM workflows using the OpenAI Python SDK, CrewAI, and AutoGen frameworks.
- Manage prompt versioning, embedding generation, and vector indexing to support scalable semantic search and RAG pipelines.
- Monitor LLM performance across latency, token usage, failures, and hallucination risks, ensuring consistent model quality.
- Build and maintain observability dashboards for LLM and AI endpoints using tracing, logging, and monitoring tools to ensure operational stability, reliability, and proactive issue detection.
- Monitor Azure AI and Azure ML model retirement schedules and develop mitigation plans, including model migration, endpoint upgrades, architecture adjustments, and business-impact assessment.
- Implement automated CI/CD pipelines for ML and AI workflows using GitHub Actions, Azure DevOps, or GitLab CI.
- Develop and maintain REST APIs and modelserving endpoints using FastAPI, Flask, or TorchServe.
- Apply expertise in MLflow, Azure OpenAI tracing, and Azure Machine Learning for model governance, monitoring, and operational insights.
Qualifications
- Bachelor's degree in Computer Science or another quantitative field
- 6+ years in software or ML engineering; 2+ years building GenAI apps.
- Expertise in Python or TypeScript/Node.js and backend architecture.
- Deep experience with Azure OpenAI, Azure AI Search, and vector databases.
- Proven track record integrating Snowflake and enterprise systems (SAP, SharePoint).
- Strong knowledge of security, compliance, and cost optimization in cloud environments.
- Leadership experience in mentoring and guiding engineering teams.
