If you love building data systems that actually hold up in production, this role is built for you. AbsenceSoft is looking for a Data Engineer to power AI and ML workloads with reliable, secure, scalable pipelines, from raw data all the way to embeddings and retrieval.
About AbsenceSoft
AbsenceSoft builds secure, intuitive leave and accommodations technology that helps employers handle complex, human moments at work with more clarity and care. The team is remote-first, values-driven, and focused on delivering outcomes that matter.
Schedule
- Remote (United States)
- Full time
- Salary range: $152,000–$190,000 USD
What You’ll Do
- Design, build, and maintain data pipelines for structured, semi-structured, and unstructured data
- Develop and optimize data models, ETL processes, and batch/streaming infrastructure
- Partner with data scientists to support training, evaluation, and deployment of ML and LLM models
- Implement scalable architectures for embeddings, vector databases, and retrieval pipelines
- Enable real-time and offline analytics workflows
- Ensure data quality, lineage, observability, and governance across data products
- Deploy secure, cloud-native infrastructure (AWS, Azure, GCP) for high-volume AI workloads
- Contribute to feature store and MLOps platform design for continuous learning and model updates
- Support Responsible AI workflows, including compliant data usage and access controls
- Evaluate new tools and tech to improve performance, reliability, and agility
What You Need
- 5+ years building large-scale, production-grade data pipelines as a Data Engineer
- Strong SQL and Python skills
- Experience with distributed processing (Spark, Flink, Beam)
- Hands-on with ELT/ETL + orchestration (Airflow, dbt, Prefect, Dagster)
- Familiarity with cloud data platforms (Snowflake, BigQuery, Redshift, Databricks)
- Experience supporting ML/AI workloads in partnership with model teams
- Knowledge of vector databases and embedding workflows (FAISS, Pinecone, Weaviate)
- Understanding of privacy, access controls, and compliance in regulated environments
- Comfort with modern DevOps for data infra (Docker, Terraform, CI/CD)
- Able to work autonomously in a fast-moving, collaborative environment
Benefits
- Comprehensive benefits
- Performance-based bonus program
- Equity opportunities
- Flexible time off and paid holidays
- Remote-first flexibility and a results-driven culture
- Learning resources, leadership programs, and growth opportunities
- Inclusive culture focused on shared wins and shared success
If you’re the person who can make AI teams faster by making the data foundation rock solid, this is a strong fit.
Happy Hunting,
~Two Chicks…