Software Systems Engineer AI Tooling & Platform
Listed on 2026-10-02
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Software Development
AI Engineer (Applied/Software), DevOps, Python, Software Engineer
Skills:
Claude Code / Agentic AI Development (Expert), Python Software Development & Automation (Expert), Git Hub / CI/CD & Release Engineering (Advanced), RAG / Knowledge Base & AI Systems (Advanced), Secure Data & Systems Integration (Advanced) Contract Type: W2 Only Duration: 6+ Months
Location:
Remote Pay Range: $75 - $80 on W2
The ISD team is seeking a hands-on Software Systems Engineer Senior Associate to own and evolve an internal AI-enabled tooling platform built around Claude toolkits, Python libraries, SharePoint, Smartsheet, dashboards, and an Obsidian-based knowledge system. The engineer will help transition the platform from a shared, non-version-controlled environment into a maintainable engineering platform that can be used by the broader team. Key areas include Claude Code and agent development, Git Hub migration and CI/CD, token-efficient tool architecture, AI/RAG systems, secure data boundaries, knowledge-base access, and reusable documentation.
This is a hands-on engineering role where the primary deliverables are working code, tested systems, automation, and documentation that non-engineering team members can follow and operate.
Own and extend the existing Python toolkits, Claude agents, dashboards, SharePoint integrations, and Smartsheet integrations supporting the ISD team. Measure current Claude/toolkit token usage and establish a baseline, then redesign routine workflows using MCP servers, packaged plugins, Agent SDK services, or internal applications to reduce unnecessary context consumption. Lead migration of the shared library into Git Hub, including repository architecture, branching strategy, CI/CD, packaged releases, and distribution processes.
Establish secure boundaries ensuring customer pricing data, deal content, knowledge-base information, and published outputs remain in approved client’s systems and are not committed to source control. Develop scanning and controls to prevent confidential data and secrets from entering repositories while enabling users to install and run releases from a fresh machine. Improve the ISD Brain knowledge base into a multi-user retrieval and contribution system with access controls, source citations, confidence levels, and grounded responses.
Build and maintain AI/agent workflows that provide cited, provenance-aware answers and explicitly return "I don't know" when sufficient evidence is unavailable. Create clear design documentation, runbooks, technical documentation, and user-facing instructions so the broader team can operate and maintain the platform.
Skills:
Deep hands-on experience with Claude Code, including skills, sub-agents, CLAUDE.md instructions, hooks, permissions, MCP connectors, and understanding of token/context behavior. Strong Python development and testing experience, preferably using the standard library and maintaining lightweight, portable solutions. Experience migrating existing codebases into Git Hub, establishing repository structures, branching strategies, CI/CD pipelines, release processes, and secure data-management practices. Production experience building agentic AI and RAG systems, including agent boundaries, retrieval, source grounding, citations, and evaluation.
Strong understanding of confidential data handling, access controls, secrets management, provenance, and secure separation of code from customer/business data. Strong communication and collaboration skills, with the ability to translate technical solutions into measurable business value. Experience managing technical backlogs and creating design documents, runbooks, and technical documentation.
Skills:
Obsidian or comparable Markdown-based knowledge bases at team scale. SharePoint and Microsoft 365 integrations/connectors. Smartsheet and Confluence. API and MCP connectivity development. GCP or AWS experience. Experience with multi-user knowledge systems and role-based access models.
Preferred Qualifications:Experience building internal developer platforms or AI-enabled productivity/tooling platforms for non-engineering users. Strong understanding of software distribution, dependency management, packaging, and fresh-machine setup. Demonstrated ability to establish measurable baselines and quantify improvements in cost, execution time, reliability, or user adoption. Strong attention to data provenance, source confidence, access restrictions, and auditability. Ability to work independently, challenge unclear…
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