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Job Role - Senior Generative AI Engineer - Vice President Job Location - Chennai Senior Generative AI Engineer - Vice President is a senior management level position responsible for accomplishing results through the management of a team or department in an effort to establish and implement new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to drive applications systems analysis and programming activities.
Responsibilities:
- Manage one or more Applications Development teams in an effort to accomplish established goals as well as conduct personnel duties for team (e.g. performance evaluations, hiring and disciplinary actions)
- Utilize in-depth knowledge and skills across multiple Applications Development areas to provide technical oversight across systems and applications
- Review and analyze proposed technical solutions for projects
- Contribute to formulation of strategies for applications development and other functional areas
- Develop comprehensive knowledge of how areas of business integrate to accomplish business goals
- Provide evaluative judgment based on analysis of factual data in complicated and unique situations
- Impact the Applications Development area through monitoring delivery of end results, participate in budget management, and handling day-to-day staff management issues, including resource management and allocation of work within the team/project
- Ensure essential procedures are followed and contribute to defining standards negotiating with external parties when necessary
- Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency, as well as effectively supervise the activity of others and create accountability with those who fail to maintain these standards.
Must to have 9-15 years hands-on experience as Generative AI Engineer with proven expertise of building and deploying AI agents, LLM integration, RAG pipelines, prompt engineering and the end-to-end MLOps lifecycle. Frameworks like Lang Chain and Auto Gen Key Responsibilities:
-
- AI Agent Development:
Build and orchestrate AI agents using frameworks like Lang Chain, Auto Gen, or CrewAI, implementing self-healing workflows (e.g., Act-Verify-Refine loops).
- LLM Integration & Backend:
Develop robust backend systems using Python and TypeScript, integrating LLMs into microservices architectures.
- Data Management for LLMs:
Utilize vector databases (Pinecone, Milvus, Weaviate) for agent memory and architect Retrieval-Augmented Generation (RAG) pipelines to enhance LLM accuracy and contextual understanding.
- Prompt Engineering:
Design and optimize prompt strategies, including automated evaluation frameworks, for high-quality LLM output.
- Context Engineering:
Manage LLM information ecosystems, including system prompts, RAG implementation, and conversation history.
- MLOps & Deployment:
Oversee the end-to-end lifecycle of generative models, focusing on inference speed, cost-efficiency, and scalability on cloud platforms (AWS, GCP, Azure).
- AI Ethics & Compliance:
Ensure adherence to security standards, IP regulations, and safety guidelines for all generative models.
- Tool Orchestration:
Define and manage the API/tool access for AI agents to optimize accuracy.
Required Skills & Qualifications:
- Technical Proficiency:
Strong command of Python, Py Torch, Tensor Flow, and Hugging Face libraries.
- GenAI Experience:
Hands-on experience with Lang Chain, Llama Index, vector databases, and fine-tuning techniques (LoRA, QLoRA).
- API & Backend:
Proven ability to integrate AI models into web applications via APIs (OpenAI, Anthropic).
- Software Engineering:
Solid understanding of software engineering best practices, including Git, CI/CD, and Docker.
Preferred Qualifications:
- Experience with multimodal AI models (image, video, audio generation).
- Published AI/LLM research or contributions to open-source AI projects.
- Background in AI governance or safety policy development.
Education:
- Bachelor’s degree/University degree or equivalent experience
- Master’s degree preferred
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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.
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
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Citigroupについて

Citigroup
PublicCitigroup Inc. or Citi is an American multinational investment bank and financial services company based in New York City. The company was formed in 1998 by the merger of Citicorp, the bank holding company for Citibank, and Travelers; Travelers was spun off from the company in 2002.
10,001+
従業員数
New York City
本社所在地
$86B
企業価値
レビュー
3.7
10件のレビュー
ワークライフバランス
4.0
報酬
2.8
企業文化
4.2
キャリア
3.5
経営陣
3.3
68%
友人に勧める
良い点
Good work-life balance
Supportive management and colleagues
Good benefits
改善点
Low/uncompetitive salary and pay
Poor management and lack of direction
Heavy workload and long hours
給与レンジ
38件のデータ
Mid/L4
Senior/L5
Mid/L4 · BUSINESS ANALYTICS SENIOR ANALYST
3件のレポート
$117,000
年収総額
基本給
$120,800
ストック
-
ボーナス
-
$117,000
$117,000
面接体験
3件の面接
難易度
3.3
/ 5
期間
14-28週間
体験
ポジティブ 0%
普通 33%
ネガティブ 67%
面接プロセス
1
Application Review
2
HR Screen
3
Technical Assessment
4
Hiring Manager Interview
5
Final Round Interview
6
Offer Decision
よくある質問
Technical Knowledge
Behavioral/STAR
Past Experience
Problem Solving
Culture Fit
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