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Senior AI Engineer
aPriori TechnologiesSenior AI Engineer developing next-generation data platforms leveraging AI capabilities at aPriori. Collaborating with teams to design scalable AI infrastructure and implement production-grade solutions.
Tech Stack
Tools & technologiesAirflowAzureCloudETLGoogle Cloud PlatformKafkaPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- 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
What you’ll need- 7+ years of professional software engineering experience
- 3+ years experience in traditional AI/ML
- 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)
- Hands-on familiarity with Prompt Engineering by leveraging LLM frameworks such as LangChain
- Strong programming skills in Python
- 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
- 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
- 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.
Benefits
Comp & perks- pension match
- private medical & dental
- flexible time off
- aPriori days
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI/MLLLM Application DevelopmentPrompt EngineeringMLOpsData EngineeringETL/ELTCI/CD for MLModel MonitoringDrift DetectionEvaluation Metrics
Soft Skills
CollaborationCommunicationMentoring
Certifications
Bachelor’s in Computer ScienceMaster’s in AI/MLMaster’s in Data Science