Senior Engineer, Data and AI

Cisive • Remote - Maryland, MD

7d

About The Position

This position has a wide range of responsibilities that includes both data and AI engineering. They will be responsible for designing and implementing data infrastructure to extract, clean, move and store data. They will need the ability to independently develop AI/ML systems and products for both internal and external use. They will communicate with business stakeholders to understand their needs and develop solutions to address them.

Requirements

• Strong Python skills for building, training, and deploying both traditional ML models and modern AI applications — including LLM-based systems, RAG pipelines, and agentic workflows.
• Proficiency in feature extraction/transformation and model selection, training, and evaluation.
• Experience with LangChain and LangGraph for building agentic/AI workflows, and working with LLM APIs such as the Claude and OpenAI SDKs.
• Proficiency building and serving APIs with FastAPI, using Pydantic for data validation and schema enforcement.
• Solid grounding in statistical methods and experimental design (e.g., hypothesis testing, regression, causal inference) to validate models and ensure sound decision-making.
• Experience deploying, monitoring, and maintaining models and AI systems in production, using tools such as MLflow (experiment tracking) and LangSmith/LangFuse (LLM tracing and evaluation).
• Discover and characterize source data systems, understand and model the underlying business concepts, and build data models that organize data to meet operational and reporting needs.
• Proficiency with databases (T-SQL, NoSQL) — writing and optimizing tables, queries, and indexes for scalability, reliability, and performance.
• Design and implement pipelines to move and transform data between systems.
• Experience with data warehousing concepts and platforms like Databricks; familiarity with Spark and Python for large-scale data processing.
• Knowledge of cloud services, particularly Azure, for scalable data storage and processing.
• Awareness of data quality, privacy, security, and compliance best practices.
• Degree in Computer Science, Physics, Mathematics, or a similar field.
• 3–5 years of experience as a data engineer, ML engineer, AI engineer, AI infrastructure engineer, or in a similar role.

Nice To Haves

• Experience self-hosting and serving models with vLLM is a plus.
• Master's degree a plus.

Responsibilities

• Designing and implementing data infrastructure to extract, clean, move and store data.
• Independently develop AI/ML systems and products for both internal and external use.
• Communicate with business stakeholders to understand their needs and develop solutions to address them.
• Building, training, and deploying traditional ML models and modern AI applications — including LLM-based systems, RAG pipelines, and agentic workflows.
• Feature extraction/transformation and model selection, training, and evaluation.
• Building and serving APIs with FastAPI, using Pydantic for data validation and schema enforcement.
• Deploying, monitoring, and maintaining models and AI systems in production.
• Discover and characterize source data systems, understand and model the underlying business concepts, and build data models that organize data to meet operational and reporting needs.
• Designing and implementing pipelines to move and transform data between systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior