Mid-Level Python AI Software Engineer [$308k/yr+] TS/SCI-FS Poly

SYSTOLIC, INC.

Annapolis Junction, MD, United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Compensation

$308,000.0

Working hours

Regular working hours

Job source

www.clearancejobs.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Databases Relational Databases Decision Support Systems Elasticsearch Python (Programming Language) Software Architecture Computer Network Operations Large Language Models Grafana Virtual Agents

+2 more

Kibana Data Pipelines

Job description

Lead development of decision support platforms for Computer Network Operations.
Design Python services for agent orchestration and Model Context Protocol servers.
Build data pipelines and implement search and observability tools using Elasticsearch, Kibana, and Grafana.
Manage databases and provide leadership through architecture decisions and developer mentorship.
Apply LLMs, RAG systems, and agentic AI to solve complex operational challenges., * Build AI-powered decision support for operators and analysts in Computer Network Operations (CNO).
Develop an AI Copilot and Deep Research Agent to query disparate data sources and synthesize actionable answers.
Work within a team of 8-12 developers to deliver custom UI, MCP Server, and AI agents.
Design and maintain Python services for AI agents and orchestration.
Build data pipelines and integrations across operational data sources.
Develop search and observability tooling using ElasticSearch, Kibana, and Grafana.

Requirements

Degree: Technical bachelor’s degree or equivalent experience
Years of experience: 12+ years
Total Compensation: $308k+ yearly, * Lead technical design discussions, architectural decisions, and mentor junior developers.
Advanced proficiency in Python for building production-grade services and APIs.
Experience with relational databases such as RDS.
Experience or interest in emerging AI technologies, including LLMs, RAG systems, and AI agent frameworks.
Familiarity with Model Context Protocol (MCP) or similar tool-orchestration frameworks.
Experience with production CNO capabilities and operations.
Strong communication skills for technical and non-technical audiences.