Senior AI Engineer - Vice President
At a glance
VP-level AI Engineering role at Citi. Pune Maharashtra India · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build the AI platform from the ground up to support multiple tenants across enterprise use
- Create coordinated AI agents, retrieval pipelines and chat interfaces to process financial adjustments end to end
- Develop resilient API-based services on cloud infrastructure using OpenShift or Kubernetes
- Put human review, audit trails, safety controls and secure delivery practices into the platform
- Lead engineering teams, set technical standards and encourage adoption across functions
What you bring
- At least ten years of experience overall, including leadership of AI/ML or platform teams delivering production systems
- Strong practical Python skills and experience building multi-agent systems, retrieval, tool use and LLM evaluation
- Deep background in event-driven systems, containerized services and Kubernetes or OpenShift
- Experience with automated CI/CD pipelines and rigorous governance and audit controls
- A computer science or engineering degree at bachelor’s or master’s level, or equivalent hands-on experience
Who this fits
This VP role suits a hands-on technical leader who can guide engineering teams while shaping and delivering AI systems. The role is hybrid in India.
From the employer
Role Overview
Join Citi Finance Technology to lead the greenfield architecture and delivery of the Intelligent, AI-Powered Adjustment Platform. You will build production-grade agentic AI workflows, NLP-driven systems, and conversational interfaces that automate complex financial adjustment processes at global enterprise scale across Wholesale and Retail businesses.
Key Responsibilities
- Greenfield Architecture: Design and build an enterprise-scale, multi-tenant AI platform from ground zero.
- Agentic Workflows: Architect multi-agent systems, tool-use loops, RAG pipelines, and conversational interfaces for end-to-end adjustment processing.
- Full-Stack & Microservices: Implement resilient, API-first microservices on cloud-native infrastructure (OpenShift / Kubernetes).
- Governance & Security: Enforce human-in-the-loop controls, auditability, guardrails, and DevSecOps best practices.
- Technical Leadership: Guide engineering teams, instill engineering standards, and drive cross-functional adoption.
Qualifications & Skills
Must-Have
- Leadership: Proven track record leading AI/ML or platform engineering teams in production-driven environments with overall 10+ years experience
- Core Engineering: Strong hands-on proficiency in Python
- Agentic AI & LLMs: Hands-on experience with multi-agent orchestration (LangGraph, LlamaIndex, or equivalent), function calling, tool use, RAG, prompt/context engineering, evaluation frameworks, and guardrails.
- Distributed Architecture: Deep experience in event-driven design, containerized microservices, and Kubernetes/OpenShift.
- DevSecOps & CI/CD: Solid experience with automated CI/CD pipelines (Harness, GitHub Actions, Tekton, ArgoCD) and strict governance/audit standards.
Nice-to-Have
- Observability: Distributed tracing, logging, and metrics stacks.
- Streaming & Messaging: Kafka, Solace, or Tibco EMS/RV.
- Automation: Familiarity with low-code automation tools.
Education
- Bachelor’s / Master’s degree in Computer Science, Engineering, or equivalent practical experience.
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Applications Development------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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