Senior Agentic AI Engineer - Vice President

Citibank (Switzerland) AG; Pune District; Hybrid; Confidential; Full time

Job summary

Citibank (Switzerland) AG is seeking a Senior Agentic AI Engineer - Vice President to lead design, development, and integration of Generative AI and agentic solutions within enterprise controls platforms.

You will work on context engineering, RAG pipelines, knowledge graphs, and multi-agent orchestration, leveraging ADK and other frameworks to deliver scalable, grounded AI applications with strong governance and safety controls.

Qualifications

• Bachelor's or master's degree in CS, Data Science, AI, or related field.
• Total experience 12+ years with 5–7 years in AI/software development, including Generative AI and agentic AI.
• Experience with cloud AI platforms and production deployments.

Responsibilities

• Collaborate to design and implement generative and agentic AI solutions across enterprise Controls Technology platform.
• Architect context layering, memory management, and token efficiency for production reliability.
• Build and optimize RAG systems with hybrid search, multi-vector retrieval, and re-ranking.
• Design Graph RAG architectures for multi-hop retrieval and explainability.
• Develop agentic workflows using Google ADK and comparable frameworks; implement tool calling and memory.

Skills

foundation models & LLMs

prompt engineering

context engineering

RAG systems

knowledge graphs

multi-agent orchestration

agent harnessing

model context protocol (MCP)

A2A protocol

OpenAI / Gemini / Claude APIs

LangChain / LlamaIndex

Python

Docker

Kubernetes

AWS cloud

Education

Bachelor's or Master's in CS/Data Science/AI

Tools

Google ADK

LangGraph

CrewAI

Neo4j

ArangoDB

Docker

Kubernetes

OpenTelemetry

Job description

## Senior Agentic AI Engineer - Vice PresidentApply: Hybrid: Pune Maharashtra India: Chennai Tamil Nadu India: Full time: Posted Today: 26993138We are seeking an experienced Senior Agentic AI Engineer to help drive the design, development, and integration of state-of-the-art Generative AI and **agentic AI** solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models.**Key Responsibilities*** Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges.* Architect advanced **context engineering** strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production.* Design and implement advanced generative AI methods, including sophisticated **prompt engineering** and **Retrieval-Augmented Generation (RAG)**.* Build and optimize **RAG systems**, including hybrid search, multi-vector retrieval, and re-ranking pipelines.* Design and implement **knowledge graphs** and **Graph RAG** architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains.* Architect **agentic workflows and multi-agent systems** using **Google Agent Development Kit (ADK)** and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer.* Design robust **agent harnesses** — governance, constraints, feedback loops, state/session management, and execution controls that make long-running agent systems reliable and safe.* Integrate agents with tools and data via the **Model Context Protocol (MCP)** and orchestrate inter-agent collaboration and task delegation via the **Agent2Agent (A2A)** protocol.* Support the integration of GenAI and agentic applications into production environments, ensuring robust deployment, scalability, observability, and maintainability.* Contribute to the development and optimization of real-time and streaming AI solutions.* Stay current with the latest advances in generative and agentic AI and actively share knowledge with the team.* Ensure adherence to ethical AI guidelines, guardrails, agent isolation/sandboxing, data privacy, and compliance standards.* Mentor junior team members, provide code reviews, and foster a culture of technical excellence.**Required Technical Skills*** Deep, hands-on expertise in **core generative AI concepts** — foundation models, LLMs, embeddings, tokenization, and context-window management.* Advanced skills in **prompt engineering** and **context engineering**, including familiarity with prompt design tools/frameworks and dynamic context orchestration.* Strong experience building **RAG systems**, including chunking strategies, hybrid search, and multi-vector retrieval.* Practical experience designing **knowledge graphs** and **Graph RAG** pipelines (e.g., using graph databases such as Neo4j or ArangoDB) for relationship-aware, multi-hop retrieval.* Proven experience building **agentic AI systems** with **Google ADK** and/or comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI, OpenAI Agents SDK), including tool/function calling, planning, and memory.* Strong grasp of **multi-agent orchestration** patterns (supervisor/worker, hierarchical, peer-to-peer) and **harness engineering** (governance, feedback loops, execution controls, agent isolation/sandboxing).* Hands-on experience with **agent interoperability protocols** — the **Model Context Protocol (MCP)** for tool/data access and the **Agent2Agent (A2A)** protocol for inter-agent collaboration.* Experience with **agent observability and evaluation** (e.g., tracing, OpenTelemetry-based tooling) for production agent systems.* Proficiency with **major GenAI APIs** (OpenAI, Gemini, Claude, etc.) and orchestration frameworks such as **LangChain and LlamaIndex**.* Strong skills in **NLP** (NER, dependency parsing, text classification, topic modeling).* Proficiency with **vector databases** and embedding models for large-scale retrieval.* Experience with containerization (**Docker**), orchestration (**Kubernetes**), and CI/CD pipelines for AI/agentic applications.* Solid understanding of AI compliance, guardrails, and responsible AI practices.* Strong skills in **Python** and experience with data preprocessing, document ingestion, and API development.**Required Soft Skills*** Strong collaboration skills to work effectively in cross-functional teams.* Analytical and proactive approach to problem-solving.* Clear communication skills for both technical and non-technical audiences.* Eagerness to learn, innovate, and mentor less experienced developers.**Qualifications*** Bachelor's or master's degree in Computer Science, Data Science, AI, or a related field.* Total experience-12+ yrs. 5–7 years of experience in AI/software development, including significant experience in Generative AI and agentic AI.* Demonstrated portfolio of successful AI-driven projects in a business environment.* Experience working with AWS (or equivalent) cloud infrastructure for AI/GenAI.