Mid-Level AI Data Engineer

Global C2 Integration Technologies

About The Position

Global C2 Integration Technologies is looking for a talented and enthusiastic Mid-Level AI Data Engineer to support our growing AI, Data, and Automation portfolio in support of federal and DoD missions. This role serves as a technical cornerstone within project teams, applying strong data engineering fundamentals to enable generative AI, large language models (LLMs), and agentic AI solutions. The ideal candidate is hands-on, mission-focused, and comfortable operating in cloud-native environments.

Requirements

S. Citizenship with eligibility to obtain and maintain a DoD Secret clearance.
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Engineering, or a related discipline.
3-7 years of hands-on experience delivering data engineering, AI, or ML solutions.
Strong understanding of ETL/ELT processes and enterprise data platforms, including experience with technologies such as:
OpenSearch / Elasticsearch
Kafka
AWS Bedrock, Glue, S3, RDS, EBS, Glacier
Databricks, Snowflake
Experience with vector databases, embeddings, and associated data structures, file formats, APIs, and services (e.g., FAISS, PGVector, OpenSearch/Elasticsearch, Pinecone, Hugging Face, Bedrock Knowledge Bases).
Practical experience working with generative AI, LLMs, tool calling (MCP), and agent-based architectures (A2A).
Familiarity with leading AI platforms and APIs (OpenAI, Anthropic, Gemini, AWS Bedrock, Google Vertex AI).
Experience using CI/CD pipelines (GitHub, GitLab, Jenkins).
Proficiency with modern development environments (VS Code) and AI-assisted coding tools (e.g., Cline, Claude Code).
Strong written and verbal communication skills with a customer-focused mindset.

Nice To Haves

Demonstrated curiosity and willingness to experiment with emerging AI capabilities in pursuit of real mission impact.
Strong Python proficiency and experience with libraries/frameworks such as:
PySpark, Pandas, uv, Pydantic, FastAPI
LangChain, LangGraph, CrewAI, Unstructured
Experience with Infrastructure as Code tools (Terraform, OpenTofu, AWS CDK, CloudFormation).
Experience with agentic AI frameworks and platforms (Agent2Agent Protocol, AWS Bedrock Agents, Mastra, CrewAI, Strands, AgentCore).
Exposure to adjacent disciplines including data science, cloud engineering, platform engineering, or UI/UX development.
Familiarity with federal cybersecurity requirements and frameworks (RMF, FedRAMP, NIST).

Responsibilities

Design, build, and optimize data pipelines to ingest, clean, normalize, and structure data for generative AI, LLMs, and Retrieval-Augmented Generation (RAG) use cases.
Enable reliable, secure access to structured and unstructured data sources supporting AI workflows.
Manage and organize large-scale datasets across cloud platforms (AWS, Azure, GCP).
Implement and maintain medallion architectures (Bronze/Silver/Gold) to ensure data quality, lineage, governance, and accessibility.
Work with SQL and NoSQL databases to model, query, and load large datasets at scale.
Monitor, tune, and maintain high-performance data stores supporting analytics, AI workloads, and reporting.
Collaborate closely with data engineers, software engineers, AI engineers, and data scientists to develop operational, agentic AI systems.
Participate in technical design reviews and cross-functional solutioning.
Support automated deployment pipelines using Infrastructure as Code (IaC), CI/CD frameworks, and containerized environments.
Contribute to repeatable, secure, cloud-native deployment patterns.
Monitor AI-enabled systems post-deployment.
Perform performance tuning and apply best practices for scalability, reliability, and availability.
Develop clean, maintainable, and well-documented code aligned with industry best practices and federal standards.
Support reproducible development and operational transparency.
Stay current on emerging AI, data engineering, and automation technologies.
Actively learn from senior engineers and AI architects through mentorship and technical collaboration.