
Software Engineer (SWE), Level 3 [D.26.0196] with Security Clearance
Why this role stands out
This hybrid Software Engineer role at Dover Networks offers an exceptional opportunity to architect and deploy cutting-edge AI-integrated Python pipelines, leveraging your expertise in LLMs to drive mission-critical initiatives with a competitive salary and robust 401(k) contributions. You'll thrive here if you possess a deep understanding of AI, Python, and complex technical data, enjoying a dynamic development lifecycle and impactful work that requires a Top Secret/SCI clearance. Apply now to join a forward-thinking team and contribute to innovative solutions in a highly secure environment.
Quick overview
Job description
Applicants must already hold a TS/SCI clearance with a current Full Scope Polygraph before applying. We are not sponsoring or processing clearances for this position. Candidates who are seeking to obtain a clearance do not meet the minimum requirements.
Salary Range: $260k-$285k per year with an additional $65k-$71k in immediately vested company 401(k) contributions Description: As a hybrid Analyst/Developer, you will utilize your experience in LLM's and AI-Integrated Python pipelines to drive mission-critical initiatives. You will be part of every aspect of the development lifecycle of new tools and plugins, from conceptualization to deployment. Your core focus will be architecting agentic Python automations, conducting vulnerability research, and analyzing complex technical data. Furthermore, you will be responsible for innovating and documenting new tradecraft and managing strategic customer outreach.
Responsibilities
- Design and deploy agentic AI workflows that leverage autonomous planning and tool-use to streamline internal operations and improve system efficiency.
- Design, develop, and maintain automated workflows using Python.
- Conduct vulnerability analysis.
- Develop and document tradecraft.
- Execute on customer requests.
- Perform customer outreach.
Skills Requirements
- Deep experience leveraging LLM's to solve complex problems, including expertise in prompt engineering and model optimization.
- Proven ability to integrate AI into automated pipelines and production workflows using API's and orchestration tools.
- Strong Python experience.
- Data parsing/manipulation.
- Networking knowledge and protocols.
- Experience with open source research.
- Knowledge of end-to-end SIGINT collection and analysis systems.
- Familiarity with Git.
- Atlassian Tools (Jira, Confluence). Nice to Haves: Experience with production CNO capabilities and operations.
YOE Requirement: 12 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.
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