{"id":954978,"url":"https://alion.io/job/jpmorganchase-lead-security-engineer-dotnet-core-docker-kubernetes","title":"Lead Security Engineer - Dotnet Core, Docker, Kubernetes","company":{"id":257,"name":"JPMorganChase","domain":"jpmorganchase.com","url":"https://alion.io/company/jpmorganchase","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":91,"open_postings":1184,"ghost_share":0.007,"stale_share":0.506,"repost_share":0.055,"time_to_fill_p50_days":9,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Security","role_family":"Security","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Columbus, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":154000,"max_usd":319000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":398},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Bitbucket","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Copilot","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Jenkins","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"MS SQL","optional":false},{"name":"SQL","optional":false},{"name":"Threat Modeling","optional":false},{"name":"Blazor","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"Entity Framework Core","optional":true},{"name":"Function Calling","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"Kubernetes","optional":true},{"name":"RAG","optional":true}],"status":"closed","first_seen_at":"2026-07-20T18:19:01Z","employer_posted_date":"2026-09-21","last_verified_at":"2026-10-21T15:04:56Z","board_verified":false,"closed_at":"2026-10-21T15:04:56Z","days_open":92,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":92},"description":"Join JPMorganChase's Cybersecurity Technology & Controls team and bring your security engineering expertise to an organization where your work directly protects one of the world's most complex and innovative financial institutions. As a Lead Security Engineer, you will work at the intersection of security, modern software development, and artificial intelligence - building solutions that matter at a global scale. Here, your contributions will shape the security posture of the firm while advancing your career alongside some of the most talented engineers in the industry.\nAs a Lead Security Engineer at JPMorganChase within Cybersecurity Technology & Controls, you will serve as a seasoned contributor on a team dedicated to delivering secure, high-quality software solutions that prevent misuse, circumvention, and malicious behavior across the firm. You will apply your deep technical expertise to design and build tamper-proof, audit-defensible security solutions across multiple technology domains in support of the firm's business objectives. 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probability and impact of security risks and proactively identify hidden problems and patterns within systems and use those insights to drive measurable improvements to coding hygiene and system architecture\nProduce architecture and design artifacts for complex applications, ensuring design constraints are met throughout the engineering lifecycle\nLeverage AI-assisted development tools such as GitHub Copilot to accelerate secure software delivery, including code refactoring, test generation, and code review support, while maintaining secure coding standards and developer accountability\nSupport the delivery of agentic AI solutions, including threat modeling of agent behaviors, defining guardrails, and implementing approval and audit logging controls where appropriate\nLead continuity-related awareness, training, educational activities, and exercises to strengthen the team's security readiness\nApplies reuse-first, AI-assisted practices within SDLC/toolchain routines to strengthen security testing and control validation, ensuring traceability/auditability and alignment to resiliency and security expectations.\nRequired qualifications, capabilities, and skills\nFormal training or certification on security engineering concepts and 5+ years applied experience\nProficiency in C# on .NET 6 or later and SQL Server/T-SQL for enterprise application development\nSolid understanding of the Software Development Life Cycle and hands-on experience with version control and pipeline tools such as Git, Bitbucket, GitHub, or Jenkins\nStrong working knowledge of information and network security, IT risk management, and architectural concepts and patterns\nDemonstrated understanding of agile methodologies, continuous integration and delivery practices, and application resiliency principles\nExperience applying specialized development and security tools such as Visual Studio and code quality analysis platforms.\nDemonstrated experience using enterprise-authorized AI capabilities within the work environment to support security engineering workflows with strong validation habits and awareness of data sensitivity.\nAbility to review and validate AI-assisted code/security recommendations before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations.\nProficiency using AI-assisted development tools, including GitHub Copilot, for code generation, refactoring, test creation, and code review assistance within secure usage practices\nStrong analytical and problem-solving skills with the ability to identify, interpret, and communicate complex security risks clearly\nPreferred qualifications, capabilities, and skills\nExperience designing and delivering agentic AI solutions, including multi-step workflows, tool and function calling, and human-in-the-loop approval patterns\nFamiliarity with GenAI solution patterns such as retrieval-augmented generation, embeddings and vector search, and document ingestion 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