C
Lead Gen AI Engineer - Vice President
Citi
2 hours ago
Full-time
On-site
East New York, New York, United States
Lead Gen AI Engineer - Vice President
Location(s):
Pune, Maharashtra, India Job Type:
Hybrid Discover your future at Citi
Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact. Job Overview
We are seeking an experienced Senior Generative AI Developer 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. 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. Time Type:
Full time 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.
#J-18808-Ljbffr
Location(s):
Pune, Maharashtra, India Job Type:
Hybrid Discover your future at Citi
Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact. Job Overview
We are seeking an experienced Senior Generative AI Developer 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. 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. Time Type:
Full time 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.
#J-18808-Ljbffr