aPriori Technologies is seeking a Senior AI Engineer to join their Data & AI Platform Team. The role involves building a next-generation data platform, integrating AI capabilities into products, and designing production-grade AI/ML systems.
Responsibilities:
- Design and build production-ready AI/ML systems, with an emphasis on Standard Model LLM-powered product and platform features
- Leverage LLM tooling/APIs such as LangChain and MCP connectors to implement retrieval-augmented generation (RAG), copilot-assistants and agentic workflows
- Partner with Product Management and product teams to translate requirements into AI-powered capabilities that surface directly in user-facing products
- Apply MLOps and LLMOps best practices: monitoring, evaluation, prompt versioning, cost/performance optimization
- Combine traditional AI/ML with modern GenAI approaches to deliver hybrid solutions where appropriate
- Collaborate with Data Engineers to establish a scalable data pipeline that serves structured data shaped for LLM consumption, feature store data for traditional AI, and Trad/GenAI-enhanced insights for internal and customer-facing BI use cases
- Mentor and upskill peers in on core AI/ML and LLMOps practices, raising the overall AI/ML competency of the team
- Stay current with developments in GenAI, LLMOps, generative AI safety frameworks, and evaluate their potential for adoption within the platform
Requirements:
- Hands-on familiarity with Prompt Engineering by leveraging LLM frameworks such as LangChain
- Strong programming skills in Python and familiarity with modern data/ML pipelines
- Solid understanding of data engineering practices (ETL/ELT, streaming, orchestration with Airflow/Temporal, dbt, Kafka, etc.)
- Knowledge of LLMOps/MLOps practices: CI/CD for ML, model monitoring, drift detection, evaluation metrics, governance
- Strong collaboration and communication skills: able to partner with Product, Platform, and Data teams to drive AI features from concept to production
- Demonstrated ability to mentor and upskill engineers, particularly in data/ML workflows
- Skilled in designing/building/deploying/operating LLM standard model-powered features in production (chatbots, copilots, RAG systems, agents)
- Proficient in working with traditional cloud AI/ML platforms such as Amazon Sagemaker, GCP Vertex AI, or Azure ML and frameworks such as TensorFlow, PyTorch, scikit-learn
- 7+ years of professional software engineering experience, including 3+ years experience in traditional AI/ML and 1+ year experience in building LLM applications on standard models
- Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related field (or equivalent experience)