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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Credence - **Location:** McLean, VA, United States - **Experience:** Expert - **Salary:** $150,000 - $180,000 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Computing, Cloud Engineering, Continuous Integration, Data Cleansing, Information Engineering, Data Files, Data Integration, Extract Transform Load (ETL), Data Structures, Data Stores, Elasticsearch, Github, Design of User Interfaces, Python (Programming Language), Machine Learning, NoSQL, Performance Tuning, Simple Data Format, Software Engineering, SQL Databases, Software Technical Review, Enterprise Data Management, AWS Cdk, Pinecone, Google Cloud, LangChain, Claude Code, Snowflake, AgentCore, Infrastructure as Code (IaC), Agentic-AI, Gitlab, Cloudformation, Fastapi, Pandas, Amazon Relational Database Service, Pgvector, Data Lakes, Pyspark, Kubernetes, Infrastructure Automation Frameworks, Information Technology, HuggingFace, CrewAI, Data Analytics, Apache Kafka, Data Management, FAISS, Terraform, Data Pipelines, OpenSearch, Jenkins, Databricks, Agent2Agent Protocol - **Published:** November 13, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-mclean-va--765a90db-a105-4326-997e-9286ed8588eb ## About the Role Artificial Intelligence (AI), Cloud Computing, Product Lifecycle, Automation, Data Management, Data Cleaning, Data Lake, Data Sets, Data Quality, Software Engineering, * Bachelor's or Master's in Computer Science, Data/AI/ML, or a related field. * 7+ years of hands-on experience delivering Data/AI/ML solutions. * Strong understanding of ETL, ELT, and other similar data pipeline processes, as well as Enterprise Data and Storage Systems, such as experience with OpenSearch/Elastic Search, Kafka, Bedrock, Glue, DataBricks, Snowflake, AWS S3, RDS, EBS, or Glacier * Experience with vector databases, embeddings, and their affiliated data structures, file formats, services, APIs, etc (e.g. FAISS, PGVector, OpenSearch/Elasticsearch, Hugging face with Pinecone, Bedrock Knowledge Base. * Familiarity with CI/CD pipelines (GitLab/GitHub/Jenkins) * Experience with VS Code and AI extensions such as Cline and Claude Code. * Strong communication skills and client-oriented mindset. * Must be authorized to work in the United States and meet the eligibility requirements for a Public Trust clearance. Preferred * Curious and experimental about the latest innovations in AI with an orientation toward the relentless pursuit of delivering mission impact. * Python proficiency and familiarity with libraries and frameworks (Pyspark, Pandas, uv, Pydantic, FastAPI, CrewAI, LangChain, LangGraph, Unstructured). * Experience with IaC tools such as Terraform, Open Tofu, AWS CDK, or CloudFormation to deploy cloud native applications. * Experience with agentic frameworks such as Agent2Agent Protocol, AWS Bedrock Agents, Mastra, CrewAI, Strands, or AgentCore. * Exposure to adjacent skillsets such as data science, UI/UX, cloud engineering, and platform engineering to understand the entire software ecosystem. * Knowledge of federal cybersecurity, RMF, FedRAMP, or regulatory frameworks. ## Description Credence has an immediate need for a Senior AI Data Engineer to join our growing AI and Automation practice. You will be a technical anchor in our AI and Automation practice. You'll apply advanced AI and data engineering expertise to design, build, and deploy data-driven solutions. You'll drive agentic AI development lifecycles and collaborate across engineering, data, and stakeholder teams to deliver high-impact, cloud-native AI capabilities that advance federal missions. Responsibilities include, but are not limited to the duties listed below * Data Integrations Build and optimize data pipelines that prepare, clean, and structure data. * Data Lake & Warehouse Engineering Manage and organize large datasets across cloud platforms (e.g., AWS, Azure, GCP) using data lake and warehouse technologies. Implement medallion architecture (Bronze/Silver/Gold layers) to ensure data quality, lineage, and accessibility. * Database Management & PerformanceWork with both SQL and NoSQL systems to model, query, and load large-scale datasets. Monitor, tune, and maintain high-performance data stores supporting analytics and reporting. * Collaborative Engineering Work alongside data engineers, software engineers, and data scientists to develop operational agentic AI systems. * Cloud Enablement Help automate model deployment workflows using Infrastructure as Code (IaC), CI/CD pipelines, and container orchestration tools. * Production Monitoring & Optimization Monitor AI systems post-deployment, perform performance tuning, and apply best practices for reliability and scalability. * Technical Rigor & Documentation Write clean, well-documented code following industry and federal guidelines, support reproducible development. * Professional Growth Stay current on AI/ML trends and tools and actively learn from senior team members through mentorship and technical design reviews.