{"id":3506184,"url":"https://alion.io/job/campbell-global-lead-software-engineer-ai-governance-engineering","title":"Lead Software Engineer - AI Governance Engineering","company":{"id":2649833,"name":"Campbell Global","domain":"campbellglobal.com","url":"https://alion.io/company/campbellglobal","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":95,"open_postings":150,"ghost_share":0.067,"stale_share":0.187,"repost_share":0.12,"time_to_fill_p50_days":13,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Backend","role_family":"Backend","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":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":98000,"max_usd":198000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":54},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Cassandra","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"ElasticSearch","optional":false},{"name":"JavaScript","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Node JS","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Redis","optional":false},{"name":"Go","optional":true},{"name":"Hugging Face","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"TensorFlow","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-29T12:26:21Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-01T09:01:25Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Join a team where your engineering work accelerates how machine learning is built, governed, and delivered across JPMorgan Chase. You will help create platform capabilities that make it easier for teams to move from ideas to production with confidence. If you enjoy building scalable systems and improving developer experience, this role offers meaningful impact and career growth.\nAs a Lead software engineer at JPMorgan Chase within the Corporate Artificial Intelligence and Machine Learning Data Platforms team, you will build and enhance products that support the machine learning lifecycle-spanning model operations, data development (such as processing and data annotation), and governance tooling. You will collaborate closely with engineers, system architects, product managers, data scientists, and research partners to deliver reliable, secure, and user-friendly platform services.\nJob responsibilities\nBuild and enhance platform capabilities for model registries, feature registries, promotion policies, and governance tooling\nDesign and deliver services for data preparation, annotation workflows, lineage, and auditability\nDevelop cloud-native microservices and application programming interfaces to support scalable model delivery and operations\nCreate large language model-powered capabilities (prompt design, agent workflows, retrieval) to deliver grounded, reliable outcomes\nProduce architecture and design artifacts and ensure implementations meet performance, resiliency, and security constraints\nUse company-approved AI-assisted development tools to improve quality and speed, validating outputs via reviews, testing, and secure coding practices\nAnalyze telemetry and user feedback; build reporting and metrics to drive continuous improvement\nIdentify hidden issues and patterns in systems and data; improve code health, observability, and platform architecture\nRequired qualifications, capabilities, and skills\nFormal training or certification on software engineering concepts\nExperience with modern architecture patterns (such as microservices, reactive architectures, event-driven architectures)\nExperience developing and deploying large language model-powered solutions using prompt design, agent workflows, tool integration, and retrieval-augmented generation\nProgramming experience in at least two modern languages or frameworks (such as Python, Java, JavaScript, React, Node.js)\nExperience building and consuming RESTful application programming interfaces and tuning performance in large-scale applications\nExperience with cloud platforms and containerization or orchestration (such as Docker and Kubernetes)\nExperience with relational and non-relational databases (such as PostgreSQL, MongoDB, Redis, Elasticsearch, Cassandra)\nExperience with engineering practices including refactoring, design patterns, test-driven development, continuous integration and delivery, and application security\nHands-on experience using company-approved AI-assisted software development tools, with the ability to validate and refine outputs for correctness, performance, and security\nPreferred qualifications, capabilities, and skills\nProficiency in Go or Terraform for automation, tooling development, or platform service implementation.\nWorking knowledge of ML frameworks (PyTorch, TensorFlow, Hugging Face, scikit-learn) for model integration and operationalization.\nExposure to multi-cloud or hybrid cloud architectures and platform portability 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