Role: Data Scientist Premium I - AI Engineer
Location: Washington, DC
Duration: 6+ Months Long TermHybrid 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.