Job description

Serving Maryland and the Greater Washington D.C. area, SageCor Solutions (SageCor) is a growing company bringing complete engineering services and true full lifecycle System Engineering services to areas requiring (or desiring) nationally-recognized expertise in high performance computing, large data analytics and cutting edge information technologies. Active TS/SCI w/ Polygraph required. Required Technical Skills • Strong Python development skills, with experience writing production-quality, maintainable code • Hands-on experience building applications on top of existing LLMs (e.g., via APIs for commercial or self-hosted models) • Experience designing multi-agent or multi-step AI workflows, including prompt chaining, tool use, and agent orchestration (e.g., LangChain, LlamaIndex, or custom frameworks) • Strong prompt engineering skills and experience evaluating/validating LLM outputs • Experience integrating AI capabilities into existing software architectures (RESTful APIs, microservices) • Experience with the Amazon Web Services (AWS) cloud computing platform Desired Technical Skills • Experience with retrieval-augmented generation (RAG) pipelines and vector databases • Familiarity with LLM observability and evaluation tooling • Experience conducting exploratory data analysis on structured and unstructured datasets to prepare inputs for AI workflows • Familiarity with MLOps/LLMOps practices for deploying and monitoring AI capabilities at scale • Familiarity with domain knowledge surrounding government agency reporting and dissemination policies Consistent with federal and state law where SageCor conducts business, SageCor Solutions provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, or any other protected class.

Requirements

Must-haves

Active TS/SCI w/ Polygraph required.
Required Technical Skills
Strong Python development skills, with experience writing production-quality, maintainable code
Hands-on experience building applications on top of existing LLMs (e.g., via APIs for commercial or self-hosted models)
Experience designing multi-agent or multi-step AI workflows, including prompt chaining, tool use, and agent orchestration (e.g., LangChain, LlamaIndex, or custom frameworks)
Strong prompt engineering skills and experience evaluating/validating LLM outputs
Experience integrating AI capabilities into existing software architectures (RESTful APIs, microservices)
Experience with the Amazon Web Services (AWS) cloud computing platform
Desired Technical Skills
Experience with retrieval-augmented generation (RAG) pipelines and vector databases
Familiarity with LLM observability and evaluation tooling
Experience conducting exploratory data analysis on structured and unstructured datasets to prepare inputs for AI workflows
Familiarity with MLOps/LLMOps practices for deploying and monitoring AI capabilities at scale
Familiarity with domain knowledge surrounding government agency reporting and dissemination policies

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonaillmaws

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