The successful candidate will be a hands-on Python backend engineer with strong experience designing and implementing secure, scalable APIs, integrating enterprise data sources, and supporting cloud-based services on AWS.
The role requires an understanding of data modeling, metadata, and semantic data integration, along with familiarity with emerging AI integration patterns, including LLMs, retrieval-augmented generation (RAG), and Model Context Protocol (MCP).
The Engineer will work collaboratively with data architects, AI engineers, and business stakeholders to ensure the Semantic Layer provides reliable, consistent, and governed access to enterprise information.
This position is 100% remote.
Candidates must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance.
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.
- Experience developing and maintaining secure API’s within the AWS API Gateway.
- 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.
- 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.
Skills Required
- Bachelor's degree in a related field or equivalent experience
- 8+ years of experience in data architecture, data engineering, or enterprise data management
- Experience developing and maintaining secure APIs within AWS API Gateway
- 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
- Experience supporting federal agencies
- Experience with vector databases such as pgvector
- AWS certification in Data Engineering, Solutions Architecture, Machine Learning, or Generative AI
- Experience with Agile, DevSecOps, and CI/CD practices
What We Do
Anika Systems is a SBA certified 8A and EDWOSB firm. The pace at which the government is changing, there is a need for technology consulting companies that rise to those challenges by taking a fresh approach to problems, solutions that get to market faster, offer service that exceed the customers’ expectations and disrupt the status quo. Anika Systems is an outcome-driven technology consulting firm that helps federal agencies solve business problems and enable them for the future, with services and solutions spanning Data and Analytics, Intelligent Automation, IT Modernization, Application Development and Cloud Engineering. We’re a team of thinkers, lifelong learners, makers, and doers that deeply understand the Federal government customers missions and goals. Our teams are deeply connected and bring their shared experiences and insights to each and every engagement. With a Show me over Tell Me philosophy which is imbibed in our corporate DNA, we produce Minimum Viable Products (MVPs) and delight our customers with solutions, not boring "solution decks". We accomplish these MVPs in our poly-cloud based Virtual Innovation Transformation Acceleration Lab (VITAL), wherein we synthesize ideas into a business concept (intake), select ideas (assess, evaluate, decide) and implement the selected ideas using the appropriate technology (fulfillment). We specialize in building Agency-wide Centers of Excellence for Data and Analytics, Intelligent Automation and Cloud Management.
