Senior Data Engineer

This is a fully remote position, open to applicants in Virginia.

📋 Description

• Design and execute end-to-end AI features, encompassing data pipelines, Generative AI, agentic workflows, and production deployment.

• Utilize sound judgment regarding model behavior, evaluation, reliability, and the establishment of guardrails.

• Create and enhance scalable, secure data pipelines and ETL/ELT workflows utilizing Python and SQL.

• Develop systems for Generative AI, agentic, machine learning, and business intelligence leveraging RAG, embeddings, vector databases, and contemporary frameworks.

• Apply MLOps/LLMOps methodologies, including CI/CD for data workflows, automated agent assessments, and infrastructure as code.

• Uphold data security and governance standards, focusing on PII/PHI management, authentication, and role-based access control.

• Independently manage technical workstreams.

• Provide mentorship to junior engineers.

• Advocate for best practices in software engineering throughout the team.

⛳️ Requirements

• Active Secret or Top Secret clearance is mandatory.

• A minimum of 5 years of relevant professional experience in a data engineering capacity.

• Proven experience in leading technical workstreams and mentoring junior engineers.

• Demonstrated ability to promote adoption of software engineering best practices within a team setting.

• Expert-level skills in Python and SQL.

• Capability to function in polyglot environments, including Scala and Java.

• Strong background in developing Agentic AI, Generative AI, Machine Learning, and Business Intelligence systems.

• Familiarity with prompt design, retrieval-augmented generation (RAG), embeddings, vector databases, context construction, and managing production outputs.

• Experience with modern frameworks such as Spark, LangChain, Databricks, Dask, Airflow, Dagster, and Kedro.

• Proficient in implementing AI features from start to finish.

• Sound judgment regarding model behavior, evaluation, reliability, guardrails, and balancing quality, latency, and cost considerations.

• Experience in establishing data security and governance measures, including PII/PHI management, authentication, and role-based access control (RBAC).

• In-depth understanding of MLOps/LLMOps practices.

• Familiarity with CI/CD for data workflows, automated agent evaluation using LangSmith, Opik, or Langfuse, and infrastructure as code employing Terraform.

• Experience with cloud platforms including AWS, Azure, and GCP.

• Excellent time management skills and the ability to manage technical workstreams independently.

🏝️ Benefits

• Employees have the flexibility to work remotely.

• A culture that is inclusive and collaborative.

• Opportunities for continuous learning.

• Availability of mentorship opportunities.

• Engage in cutting-edge projects involving cloud-native technologies, DevSecOps, AI/ML, Generative AI, and agentic systems.