{"id":1303817,"url":"https://alion.io/job/stonex-group-software-engineering-manager-c-net","title":"Software Engineering Manager (C#/.NET)","company":{"id":2646,"name":"StoneX Group","domain":"stonex.com","url":"https://alion.io/company/stonex","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"Leadership","role_family":"Leadership","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bogotá, Colombia"],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":76000,"max_usd":195000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1275},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Angular","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude Code","optional":false},{"name":"Copilot","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub","optional":false},{"name":"Hallucination","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PostgreSQL","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-09-26T12:49:44Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-09-26T16:30:13Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Overview\nPermanent, full-time\nPlease submit your CV in English\nConnecting clients to markets - and talent to opportunity\nWith 5,400+ employees and over 80,000 institutional, commercial, and payments clients, we operate from more than 80 offices spread across six continents. As a Fortune 100, Nasdaq-listed provider, we connect clients to the global markets - focusing on innovation, human connection, and providing world-class products and services to all types of investors.\nWhether you want to forge a career connecting our retail clients to potential trading opportunities, or ingrain yourself in the world of institutional investing, StoneX Group is made up of four business segments that offer endless potential for progression and growth.\nCorporate: Engage in a deep variety of business-critical activities that keep our company running efficiently. From strategic marketing and financial management to human resources and operational oversight, you’ll have the opportunity to optimize processes and implement game-changing policies.\nResponsibilities\nPosition Purpose: We are seeking a deeply technical Engineering Manager to lead a Client Onboarding engineering team in Colombia. This is a player-coach role, not a traditional management-only position. The successful candidate will set the technical direction for the team, lead architecture and solution design, guide engineers through complex delivery challenges, and remain directly involved in the codebase.\nApproximately 70% of the role will focus on technical leadership, architecture, system design, AI enablement, engineering standards, mentoring, and delivery direction. The remaining 30% will involve hands-on individual contribution, including development of critical functionality, proof-of-concept implementation, code reviews, debugging, and production problem-solving.\nThe Engineering Manager will also lead the team’s adoption of AI-assisted and agentic engineering practices. This includes the effective use of enterprise-approved AI coding assistants, task-specific engineering agents, automated testing agents, reusable skills and workflows, and AI-supported modernization approaches.\nAI fluency is an explicit expectation of this role. The Engineering Manager should be able to distinguish between using AI to improve software delivery and embedding AI capabilities into the products and platforms the team develops.\nPrimary duties will include as per below:\nTechnical Leadership, Architecture, and Team Direction - Approximately 70%\nOwn the technical direction and solution architecture for the engineering team, ensuring alignment with enterprise standards and the broader Client Onboarding technology strategy.\nLead end-to-end system design across React applications, APIs, microservices, workflow components, relational and NoSQL databases, event streams, cloud infrastructure, and external integrations.\nTranslate complex business, operational, and regulatory requirements into scalable technical designs and executable engineering plans.\nProduce and review architecture diagrams, technical specifications, API contracts, data models, event schemas, integration patterns, and implementation approaches.\nDrive modernization initiatives involving cloud-native applications, microservices, event-driven architecture, containerization, platform engineering, and legacy application transformation.\nAct as the team’s primary technical escalation point for architecture, design, development, integration, performance, security, and production issues.\nLead technical design reviews and code reviews while ensuring key architectural decisions are documented and understood by the team.\nEstablish and reinforce engineering standards covering code quality, automated testing, CI/CD, security, observability, resilience, performance, and maintainability.\nEnsure non-functional requirements-including scalability, availability, recoverability, security, auditability, and monitoring-are incorporated into solution designs from the outset.\nIdentify and mitigate architectural risks, technical debt, delivery bottlenecks, system inefficiencies, and cross-team dependencies.\nBreak complex initiatives into clear technical deliverables and provide engineering estimates, implementation sequencing, dependency analysis, and delivery guidance.\nMentor developers and technical leads, helping them strengthen their architecture, system design, coding, testing, troubleshooting, and production-support capabilities.\nPromote a culture of technical ownership, experimentation, continuous improvement, knowledge sharing, and engineering excellence.\nAI and Agentic Engineering Leadership\nDefine and drive the team’s strategy for using AI across the software-development lifecycle, including requirements analysis, solution design, coding, testing, documentation, code review, modernization, debugging, and incident investigation.\nPromote the responsible use of enterprise-approved AI development tools such as GitHub Copilot, Claude Code, or equivalent platforms.\nIdentify opportunities to use agentic AI to automate repeatable engineering activities, including:Code generation and refactoring.\nLegacy-code analysis and modernization.\nUnit, integration, and end-to-end test creation.\nPull-request analysis and code-quality checks.\nAPI and technical-documentation generation.\nDependency and vulnerability analysis.\nProduction-log investigation and root-cause analysis.\nApplication onboarding, configuration, and repository setup.\n\nDesign reusable AI engineering assets, including prompts, instructions, skills, rules, agent definitions, workflows, reference implementations, test suites, and evaluation criteria.\nEstablish a centrally governed approach for distributing approved AI guardrails and reusable agent capabilities across engineering repositories.\nLead proof-of-concept initiatives to validate AI-assisted development approaches before broader adoption.\nEvaluate where agentic workflows provide measurable value and where deterministic software, traditional automation, or human review remains more appropriate.\nEstablish human-in-the-loop controls for AI-generated code, designs, tests, documentation, and production recommendations.\nEnsure AI-assisted engineering complies with enterprise requirements for security, data privacy, intellectual property, access control, auditability, and regulatory compliance.\nDefine standards for reviewing and validating AI-generated output, including automated testing, security scanning, peer review, traceability, and approval requirements.\nMeasure the impact of AI adoption through tangible engineering outcomes such as delivery cycle time, development effort, test coverage, defect rates, rework, maintainability, and production stability.\nEvaluate new models, agent frameworks, developer tools, orchestration platforms, and AI engineering patterns while avoiding unnecessary vendor lock-in.\nProduct and Platform AI Capabilities\nIdentify appropriate opportunities to embed AI or machine-learning capabilities within Client Onboarding products and internal platforms.\nGuide the architecture of AI-enabled solutions using relevant patterns such as large language models, retrieval-augmented generation, vector search, structured output, tool or function calling, and workflow orchestration.\nEnsure AI-enabled product capabilities include appropriate safeguards for accuracy, explainability, auditability, data protection, and human oversight.\nDefine evaluation approaches for AI capabilities, including expected behavior, accuracy thresholds, failure conditions, regression testing, and operational monitoring.\nPartner with Product, Architecture, Information Security, Compliance, and Data teams when evaluating or implementing AI-enabled functionality.\nEngineering and Delivery Leadership\nPartner with Product and Quality Engineering to ensure requirements, acceptance criteria, testing strategies, and implementation plans are aligned before development begins.\nCoordinate with Architecture, Cloud Engineering, DevOps, Information Security, and other engineering teams to resolve dependencies and deliver integrated solutions.\nMaintain a strong focus on delivery while balancing strategic architecture, platform modernization, technical debt, AI experimentation, and operational responsibilities.\nProvide appropriate people leadership, including setting expectations, providing technical feedback, supporting career development, contributing to hiring, and addressing performance concerns.\nHands-On Individual Contribution - Approximately 30%\nDesign, develop, test, and maintain production-grade functionality using React, TypeScript, C#, and .NET Core.\nContribute directly to critical code paths, shared frameworks, complex integrations, and technically challenging features.\nCreate reference implementations that demonstrate the expected architecture, coding standards, testing practices, and AI-assisted development approach.\nPersonally use approved AI development tools to accelerate implementation while maintaining accountability for the quality and correctness of the final output.\nBuild and refine task-specific engineering agents, reusable prompts, agent workflows, repository instructions, and development guardrails.\nDevelop proofs of concept for agentic engineering workflows and AI-enabled product capabilities.\nExperiment with patterns such as tool calling, structured outputs, retrieval-augmented generation, AI-assisted testing, and workflow orchestration.\nTroubleshoot complex application, infrastructure, data, integration, and production issues, working with engineers to identify root causes and implement sustainable fixes.\nParticipate actively in code reviews and provide detailed, actionable feedback on architecture, design, security, performance, testability, and maintainability.\nReview AI-generated code and technical artifacts with the same rigor applied to manually produced work.\nBuild and maintain automated tests, including unit, integration, contract, component, performance, and end-to-end tests.\nContribute to CI/CD pipelines, deployment automation, application telemetry, dashboards, alerts, and operational-readiness activities.\nRemain close to the codebase and delivery process to maintain technical credibility and make informed engineering decisions.\nQualifications\nTo land this role you will need:\nBachelor’s or master’s degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience.\n12+ years of professional software-engineering experience, including significant experience building and evolving large-scale enterprise applications.\nAt least 3 years of experience as a technical lead, architecture lead, engineering manager, or equivalent technical leadership role.\nExperience designing or implementing agentic AI workflows for software engineering or enterprise applications.\nExperience creating reusable AI agents, prompts, skills, instructions, workflows, evaluation suites, or repository-level AI guardrails.\nDemonstrated ability to technically lead an engineering team while continuing to contribute directly as an individual engineer.\nExperience within Banking, Financial Services, FinTech, or another highly regulated enterprise environment.\nDeep hands-on experience building scalable web applications using React with TypeScript; strong Angular experience may also be considered.\nStrong experience designing and developing enterprise applications, APIs, and services using C# and .NET Core.\nStrong understanding of software architecture, object-oriented design, domain modeling, design patterns, and clean-code principles.\nExperience designing distributed systems and microservices, including synchronous and asynchronous integration patterns.\nStrong knowledge of event-driven architecture and messaging or streaming platforms such as Apache Kafka.\nHands-on experience with PostgreSQL, SQL Server, Kubernetes, Kafka, Azure Functions, API gateways, application-configuration platforms, and se...","description_format":"text","description_chars":14262,"description_truncated":true,"requirements":{"experience_years_min":12,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Colombia","iso":null,"kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Currency Exchange & FX Payments","Online Brokerage & Trading Platforms"],"lifecycle":[{"event":"open","at":"2026-09-26T12:49:44Z"}],"liveness":{"score":89,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.893,"p_room":1,"age_days":1,"expected_fill_days":9,"reasons":["conf:37","velocity","win:early"],"computed_at":"2026-09-28T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/stonex-group-software-engineering-manager-c-net","json_url":"https://alion.io/job/stonex-group-software-engineering-manager-c-net.json","meta":{"generated_at":"2026-09-29T00:44:56Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":657,"day_limit":5000,"remaining_today":4343,"minute_limit":60,"resets_at":"2026-09-30T00:00:00Z"}}}