About this role
Opella is seeking a hands-on AI & Data Engineer to build and deploy enterprise-grade AI capabilities for internal analytics platforms. This engineering-focused role emphasizes applied AI, prompt engineering, and data modeling to enable business teams to interact with data and generate insights. Responsibilities include: Data Engineering & Platform Integration: Building scalable pipelines using Snowflake, DBT, and Airflow; developing analytics-ready data models; and ensuring data quality. Applied AI, LLM & Prompt Engineering: Designing LLM-powered capabilities such as natural language-to-SQL generation, KPI reasoning, and metadata extraction; optimizing prompt frameworks; and integrating LLMs via AWS Bedrock, OpenAI, or Anthropic. RAG & Knowledge Systems: Engineering RAG pipelines and embedding-based retrieval systems using vector search strategies. AI Services & Architecture: Developing APIs and microservices with Python, FastAPI, and Docker; building orchestration layers for agent-based systems; and deploying scalable cloud-native AI services. Semantic Layer & Business Alignment: Integrating AI systems with governed semantic layers to ensure alignment with business KPIs. Productionization & Governance: Establishing standards for prompt versioning, monitoring, performance tracking, and secure, privacy-safe AI usage. Required Qualifications: Bachelor’s degree in Computer Science, Data Engineering, AI, or related field; 4–8 years of experience in AI/Data Engineering or Applied AI systems; strong programming skills in Python and SQL; hands-on experience with LLMs, prompt engineering, RAG pipelines, and vector search systems; and familiarity with FastAPI, Docker, and orchestration tools. Must have exposure to agent frameworks like LangChain or Autogen and experience with prompt/metadata-driven systems. Preferred Qualifications: Experience in CPG, retail, or ecommerce; familiarity with Streamlit; and advanced certifications in AWS, Snowflake, Databricks, or GCP.