C
Release Management AI Engineering Lead - SVP
Citigroup Inc
2 hours ago
Full-time
On-site
Irving, Texas, United States
Release Management AI Engineering Lead
The Department Developer Engineering is a function of the CTO organization. Our mission is to make it easy and enjoyable for software engineering teams to go from a business idea to delivering an innovative product solution. We are committed to modernizing our toolchain, streamlining delivery processes, automating at scale, and embedding intelligent controls that help engineering teams ship with confidence and speed. The Team Within the Developer Engineering department, the Developer Services group is a dedicated expert team at the forefront of the everything-as-code agenda. We exist to deliver measurable reductions in process friction, manual effort, and human error — ensuring our policies, standards, and controls are codified, automated, and consistently applied across the organization. We hold a unique mandate as part of a greenfield program to shape critical technical consensus at a global scale, transforming how Citi engineers and applies controls across its technology landscape. Developer Services is a cross-functional team of engineers, AI practitioners, data scientists, business analysts, and product managers — working together to engineer next-generation codified controls, build the underlying platforms that power them, and drive adoption across the broader organization. The Opportunity This is a rare opportunity to sit at the intersection of AI engineering, release management, and platform modernization at one of the world's leading financial institutions. As a Release Management AI Engineering Lead, you will play a pivotal leadership role in designing and delivering intelligent release management capabilities — using AI and automation to eliminate toil, de-risk deployments, and accelerate the path from code to production. You will shape the technical strategy for AI-powered release pipelines, lead a team of engineers, and partner closely with product, security, and platform teams to deliver production-grade AI systems. You will have the opportunity to work with cutting-edge Generative AI technologies — including large language models (LLMs) such as GPT-4, Gemini, and Claude — embedding intelligent capabilities directly into our release and engineering workflows through prompt engineering, agentic design, and AI-driven automation. This is not just an engineering role. It is a leadership opportunity to define how AI reshapes the release management discipline at scale. Responsibilities Release Management & Delivery Excellence Own the end-to-end release management strategy, defining standards and tooling for CI/CD, deployment orchestration, and release governance Drive the adoption of Harness, progressive delivery (blue/green, canary), and everything-as-code principles across engineering teams Define and enforce SDLC controls, ensuring release processes are secure, auditable, and compliant with Citi's standards AI Engineering & Release Intelligence Lead the design and delivery of AI-powered release management systems, including intelligent deployment gates, anomaly detection, predictive rollback, and LLM-assisted release orchestration Architect and implement agentic AI workflows that automate release readiness assessments, change risk analysis, and compliance checks Evaluate and integrate AI/ML models into production release workflows, ensuring safety, reliability, and auditability Engineering Leadership Lead, mentor, and grow a team of AI and platform engineers — fostering a culture of technical excellence, psychological safety, and continuous improvement Collaborate with cross-functional stakeholders — product managers, security engineers, platform teams, and business analysts — to align release capabilities with organizational goals Drive cultural change by championing AI-augmented engineering practices and encouraging critical, creative thinking about controls and processes Platform & Systems Engineering Design and build scalable, production-grade backend systems using Python and/or Golang, integrating with cloud-native and containerized infrastructure Ensure all platforms are secure, observable, and compliant with Citi's DevSecOps and SDLC requirements Champion best practices in system design including distributed systems, event-driven architectures, micro-services, and API-first design What We're Looking For Leadership & Mindset A strategic thinker with a hands-on approach — comfortable moving between high-level architecture and deep technical delivery A growth mindset with a genuine passion for AI, automation, and engineering innovation Strong communication and influencing skills — able to engage technical teams, senior stakeholders, and cross-functional partners with clarity and conviction An advocate for inclusion, diversity, and psychological safety in all its forms A self-starter who thrives in ambiguity, brings structure to complexity, and energizes the people around them Ways of Working Pragmatic and risk-aware, with a creative approach to solving hard engineering problems Committed to a culture of continuous improvement and data-driven decision-making Enthusiastic about knowledge sharing, mentoring, and building high-performing teams Experience & Skills Required Proven experience leading AI/ML or platform engineering teams in product-focused environments Strong hands-on engineering experience in Python and/or Golang — building and shipping production systems Demonstrated experience with Generative AI and LLM technologies — including prompt engineering, LangChain, LlamaIndex, RAG pipelines, or equivalent frameworks Deep knowledge of release management and CI/CD — including tools such as Harness, GitHub Actions, Tekton, ArgoCD, or similar Experience with agentic AI architectures, AI workflow orchestration, and integrating AI into engineering systems Proven experience with distributed systems, event-driven architectures, container-based micro-services, and cloud-native infrastructure (Kubernetes / OpenShift) Hands-on experience with DevSecOps practices, SDLC controls, and security-by-design principles Preferred Experience with MLOps platforms and model deployment pipelines (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) Familiarity with observability tooling (e.g., Grafana, OpenTelemetry, Loki, Prometheus) Exposure to policy-as-code and compliance-as-code frameworks (e.g., OPA, Rego) Experience in regulated industries (financial services, fintech) with exposure to audit, controls, or governance functions Background working in agile, product-oriented engineering teams with a continuous delivery mindset
The Department Developer Engineering is a function of the CTO organization. Our mission is to make it easy and enjoyable for software engineering teams to go from a business idea to delivering an innovative product solution. We are committed to modernizing our toolchain, streamlining delivery processes, automating at scale, and embedding intelligent controls that help engineering teams ship with confidence and speed. The Team Within the Developer Engineering department, the Developer Services group is a dedicated expert team at the forefront of the everything-as-code agenda. We exist to deliver measurable reductions in process friction, manual effort, and human error — ensuring our policies, standards, and controls are codified, automated, and consistently applied across the organization. We hold a unique mandate as part of a greenfield program to shape critical technical consensus at a global scale, transforming how Citi engineers and applies controls across its technology landscape. Developer Services is a cross-functional team of engineers, AI practitioners, data scientists, business analysts, and product managers — working together to engineer next-generation codified controls, build the underlying platforms that power them, and drive adoption across the broader organization. The Opportunity This is a rare opportunity to sit at the intersection of AI engineering, release management, and platform modernization at one of the world's leading financial institutions. As a Release Management AI Engineering Lead, you will play a pivotal leadership role in designing and delivering intelligent release management capabilities — using AI and automation to eliminate toil, de-risk deployments, and accelerate the path from code to production. You will shape the technical strategy for AI-powered release pipelines, lead a team of engineers, and partner closely with product, security, and platform teams to deliver production-grade AI systems. You will have the opportunity to work with cutting-edge Generative AI technologies — including large language models (LLMs) such as GPT-4, Gemini, and Claude — embedding intelligent capabilities directly into our release and engineering workflows through prompt engineering, agentic design, and AI-driven automation. This is not just an engineering role. It is a leadership opportunity to define how AI reshapes the release management discipline at scale. Responsibilities Release Management & Delivery Excellence Own the end-to-end release management strategy, defining standards and tooling for CI/CD, deployment orchestration, and release governance Drive the adoption of Harness, progressive delivery (blue/green, canary), and everything-as-code principles across engineering teams Define and enforce SDLC controls, ensuring release processes are secure, auditable, and compliant with Citi's standards AI Engineering & Release Intelligence Lead the design and delivery of AI-powered release management systems, including intelligent deployment gates, anomaly detection, predictive rollback, and LLM-assisted release orchestration Architect and implement agentic AI workflows that automate release readiness assessments, change risk analysis, and compliance checks Evaluate and integrate AI/ML models into production release workflows, ensuring safety, reliability, and auditability Engineering Leadership Lead, mentor, and grow a team of AI and platform engineers — fostering a culture of technical excellence, psychological safety, and continuous improvement Collaborate with cross-functional stakeholders — product managers, security engineers, platform teams, and business analysts — to align release capabilities with organizational goals Drive cultural change by championing AI-augmented engineering practices and encouraging critical, creative thinking about controls and processes Platform & Systems Engineering Design and build scalable, production-grade backend systems using Python and/or Golang, integrating with cloud-native and containerized infrastructure Ensure all platforms are secure, observable, and compliant with Citi's DevSecOps and SDLC requirements Champion best practices in system design including distributed systems, event-driven architectures, micro-services, and API-first design What We're Looking For Leadership & Mindset A strategic thinker with a hands-on approach — comfortable moving between high-level architecture and deep technical delivery A growth mindset with a genuine passion for AI, automation, and engineering innovation Strong communication and influencing skills — able to engage technical teams, senior stakeholders, and cross-functional partners with clarity and conviction An advocate for inclusion, diversity, and psychological safety in all its forms A self-starter who thrives in ambiguity, brings structure to complexity, and energizes the people around them Ways of Working Pragmatic and risk-aware, with a creative approach to solving hard engineering problems Committed to a culture of continuous improvement and data-driven decision-making Enthusiastic about knowledge sharing, mentoring, and building high-performing teams Experience & Skills Required Proven experience leading AI/ML or platform engineering teams in product-focused environments Strong hands-on engineering experience in Python and/or Golang — building and shipping production systems Demonstrated experience with Generative AI and LLM technologies — including prompt engineering, LangChain, LlamaIndex, RAG pipelines, or equivalent frameworks Deep knowledge of release management and CI/CD — including tools such as Harness, GitHub Actions, Tekton, ArgoCD, or similar Experience with agentic AI architectures, AI workflow orchestration, and integrating AI into engineering systems Proven experience with distributed systems, event-driven architectures, container-based micro-services, and cloud-native infrastructure (Kubernetes / OpenShift) Hands-on experience with DevSecOps practices, SDLC controls, and security-by-design principles Preferred Experience with MLOps platforms and model deployment pipelines (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) Familiarity with observability tooling (e.g., Grafana, OpenTelemetry, Loki, Prometheus) Exposure to policy-as-code and compliance-as-code frameworks (e.g., OPA, Rego) Experience in regulated industries (financial services, fintech) with exposure to audit, controls, or governance functions Background working in agile, product-oriented engineering teams with a continuous delivery mindset