Job Description
Anika Systems is seeking an experienced Data Architect to lead the design and implementation of enterprise data and AI platforms supporting federal clients. This role combines data architecture, cloud engineering, and AI innovation to enable data-driven decision-making and intelligent automation. This position is 100% remote.
Candidates must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance.
Key Responsibilities
- Design scalable enterprise data architectures, data lakes, warehouses, and analytics platforms on AWS.
- Develop logical, physical, and dimensional data models and establish data governance, quality, security, and metadata standards.
- Build and optimize data pipelines, ETL/ELT processes, APIs, and serverless solutions using AWS, Python, and SQL.
- Design and implement AI-enabled solutions, including RAG, LLM integrations, AI agents, and MCP-based architectures.
- Develop AI evaluation (Evals) frameworks to measure model accuracy, retrieval quality, safety, and business impact.
- Collaborate with stakeholders to translate business needs into scalable technical solutions.
- Provide architectural leadership, technology recommendations, and technical oversight across Agile teams.
Required Qualifications
- Bachelor’s degree in a related field or equivalent experience.
- 8+ years of experience in data architecture, data engineering, or enterprise data management.
- Expertise in data modeling, data integration, metadata management, governance, and AWS-based data platforms.
- Strong hands-on experience with Python, SQL, APIs, and serverless architectures.
- Experience implementing LLMs, RAG solutions, AI agents, MCP integrations, and AI evaluation methodologies.
- Knowledge of vector databases, embeddings, semantic search, and enterprise knowledge retrieval.
- Strong communication and stakeholder engagement skills.
- U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Preferred Qualifications
- Experience supporting federal agencies.
- Experience with vector databases (e.g. pgvector).
- AWS certifications in Data Engineering, Solutions Architecture, Machine Learning, or Generative AI.
- Experience with Agile, DevSecOps, and CI/CD practices.
