This role pays less than
81%
of similar roles. Most pay
$184,987–$246,150
— the shaded band above.
At the midpoint, this role pays about
$177k
versus about
$216k
for comparable roles.
Based on 240 similar postings.
Employer
About Citi
Citi is one of the world’s most trusted financial institutions, proudly serving millions of customers across the United States.
Citi currently has
256 open roles
on FindRole.
Listed pay typically runs
$140,080–$210,120
across 238 roles with salary data.
Release Management AI Engineering Lead - SVP joins the Developer Services group within the Developer Engineering department. This role focuses on designing and delivering intelligent release management capabilities by integrating AI and automation to reduce manual effort and de-risk deployments. You will lead a team of engineers to build production-grade systems, including intelligent deployment gates, anomaly detection, and agentic workflows for risk analysis. The work involves modernizing the toolchain through everything-as-code principles and advanced CI/CD orchestration. Key technologies include Python, Golang, and Generative AI models like GPT-4, Gemini, and Claude, alongside frameworks such as LangChain and LlamaIndex. You will manage infrastructure involving Kubernetes, OpenShift, and tools like Harness and GitHub Actions to solve complex release governance and compliance challenges within a regulated financial services environment using distributed systems and micro-services.
Own the end-to-end release management strategy, including CI/CD standards, deployment orchestration, and governance.
Design and deliver AI-powered systems for intelligent deployment gates, anomaly detection, and predictive rollbacks.
Architect agentic AI workflows to automate release readiness assessments and compliance checks.
Lead, mentor, and grow a team of AI and platform engineers while fostering technical excellence.
Build scalable, production-grade backend systems using Python or Golang on cloud-native infrastructure.
Integrate Generative AI technologies like LLMs into engineering workflows through prompt engineering and agentic design.
Ensure all release processes and platforms are secure, auditable, and compliant with corporate SDLC standards.
What we're looking for
13+ years of relevant experience in AI/ML or platform engineering teams within product-focused environments.
Strong hands-on experience building production systems using Python and/or Golang.
Demonstrated experience with Generative AI and LLM technologies, including prompt engineering, LangChain, LlamaIndex, and RAG pipelines.
Deep knowledge of release management and CI/CD tools such as Harness, GitHub Actions, Tekton, or ArgoCD.
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 like Kubernetes or OpenShift.
Hands-on experience with DevSecOps practices, SDLC controls, and security-by-design principles.
Experience with MLOps platforms, observability tooling, policy-as-code frameworks, or working in regulated industries (preferred).