Data Scientist Premium I

Preferred: Experience with GraphRAG, knowledge graphs, ontologies, graph databases, Azure AI services, MCP, or enterprise technology environments. The team is seeking an AI/ML Engineer to build and operationalize AI solutions across RAG, agentic workflows, knowledge graphs, and machine learning.

Role: Data Scientist Premium I - AI Engineer
Location: Washington, DC
Duration: 6+ Months Long Term
Hybrid Onsite: 4 days per week from Day 1, with a full transition to 100% onsite anticipated soon.

Background
The team is seeking an AI/ML Engineer to build and operationalize AI solutions across RAG, agentic workflows, knowledge graphs, and machine learning. The role is hands-on and spans experimentation, backend development, deployment, evaluation, and production support.

What You Will Do

• Design and build RAG and agentic AI solutions from prototype through production
• Develop AI workflows using Python, LangGraph, LangChain, or comparable frameworks
• Build backend services and APIs using FastAPI, REST APIs, and containerized deployment patterns
• Develop retrieval pipelines covering ingestion, embeddings, indexing, retrieval, reranking, grounding, and citations
• Support GraphRAG and knowledge graph use cases that combine structured and unstructured information
• Build and maintain data and AI pipelines using Databricks
• Integrate AI applications with Azure and enterprise services, including identity, security, logging, and monitoring
• Evaluate solution quality using retrieval metrics, RAG evaluations, LLM-based evaluation, and human review
• Collaborate with engineers, architects, product teams, and domain specialists to move use cases into production
• Support technical documentation, troubleshooting, optimization, and post-production improvements

What You Will Bring

• 3+ years of relevant software, data, machine learning, or AI engineering experience
• Strong programming capability in Python and experience building production APIs or backend services
• Hands-on experience with RAG, LLM applications, or agentic AI workflows
• Experience with FastAPI, REST APIs, Docker, Azure DevOps Git, and CI/CD
• Experience with Microsoft Azure and cloud-based application deployment
• Familiarity with Databricks, data pipelines, SQL, and common Python data/ML libraries
• Understanding of authentication, authorization, RBAC, secrets management, logging, and monitoring
• Experience evaluating AI systems through retrieval metrics, RAGAS or similar frameworks, or task-specific benchmarks
• Strong communication and collaboration skills across technical and non-technical teams
• Ability to take ownership and work iteratively from experimentation to secure, maintainable production solutions

Master s degree in Computer Science, Engineering, Data Science, AI/ML, Statistics, or a related technical field
Preferred: Experience with GraphRAG, knowledge graphs, ontologies, graph databases, Azure AI services, MCP, or enterprise technology environments.



EEO:

Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.