Note: The job is a remote job and is open to candidates in USA. Nucleus Security is seeking a Lead Platform Engineer, Agentic Operations to build AI-powered tools that accelerate software delivery and improve the developer experience. The role focuses on developing automated code review, testing, quality, and codebase-aware agent capabilities integrated into engineering workflows while establishing reliable, secure, measurable, and widely adopted AI-enabled developer tooling.
Responsibilities
- Build and launch AI-powered developer tools that engineers use every day, including automated PR review, code-quality gates, test generation, and codebase-aware agents
- Integrate these tools into Slack, Git, CI/CD, IDE, and internal platform workflows so code moves from development to production faster without lowering quality or security
- Measure adoption, cycle time, review load, and defects; establish benchmarks and AI evaluation frameworks to assess quality and impact, using data and developer feedback to reduce toil and continuously improve the developer experience
Skills
- Lead-level software engineering and system design with 8+ years of professional experience building production services, internal platforms, or developer tooling, with strong ownership of architecture, reliability, and technical direction
- Advanced proficiency in Python and working proficiency in at least one additional language such as TypeScript/JavaScript or Go
- Experience building CI/CD integrations, PR bots and status checks, CLIs, code-analysis pipelines, IDE integrations, or internal developer platforms - not only using AI tools as an end user
- Advanced proficiency with the use of containers – Docker and Kubernetes experience
- LLM and agent engineering with hands-on experience with prompt and context engineering, structured outputs, tool calling, RAG over codebases, agent workflows, evaluation harnesses, and productionizing AI features
- Strong knowledge of GitHub or GitLab APIs, webhooks, branch protection, required checks, custom review comments, risk scoring, and merge policies
- Experience combining linting, static analysis, automated testing, changed-code coverage, security scanning, and merge blocking into reliable delivery workflows
- Experience in unit, integration, and end-to-end testing; AI-assisted test generation; test-data creation; coverage strategy; flaky-test management; and dependable CI integration
- Code quality and application security tooling: Practical experience with tools such as SonarQube, Semgrep, CodeQL, ESLint, Ruff, SAST, dependency scanning, secret detection, supply-chain controls, and policy-as-code
- AI evaluation, guardrails, and observability: Ability to build regression suites, model-output quality measures, human-review paths, logging, metrics, tracing, and failure-analysis workflows for AI-powered systems
- Impact measurement and technical tool evaluation: Ability to instrument cycle time, review load, defect rates, AI adoption, and developer satisfaction; assess commercial tools; make build-versus-buy decisions; and turn results into priorities and ROI
- Systems and product thinking for internal customers — treats other engineers as the product's users; drives adoption, gathers feedback, iterates, and balances speed vs. Safety/governance
- 8 Year in technical with a major programming language with a preference to python
- Must be using AI in their current role or pet project
- Direct experience with AI code review or agentic coding tools in production (CodeRabbit, Cursor Bugbot, GitHub Copilot code review, Qodo/PR-Agent, Anthropic Code Review, or similar)
- Practical use of agent frameworks or orchestration tools (LangChain, LangGraph, LlamaIndex, or custom agent loops)
- Experience with risk-based or policy-driven automation (auto-approving low-risk PRs, severity scoring, or policy-as-code)
- Familiarity with observability for developer tools and AI systems (logging, metrics, tracing of AI review outcomes, evaluation dashboards)
- Prior work measuring developer productivity or DevEx impact (cycle time, review load, AI adoption metrics, or DORA-related instrumentation)
- Experience operating in regulated or high-compliance environments (security review processes, auditability of AI decisions, or governance of AI-generated code)
- Knowledge of large monorepos or multi-language codebases and the unique challenges they create for AI tooling
Benefits
- 100% company-paid health, dental, vision, life, and short-term disability insurance options
- Generous 401k contribution (not a match)
- Flexible PTO + 10 company holidays
- Paid parental leave
- Fantastic company culture
- Work on a truly unique, market-defining product
Company Overview