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

6+ years of experience in AI/software development, including significant experience in Generative AI and agentic AI.

Strong skills in

Python

and experience with data preprocessing, document ingestion, and API development.

Deep, hands‑on expertise in

core generative AI concepts

— foundation models, LLMs, embeddings, tokenization, and context‑window management.

Proficiency with

major GenAI APIs

(OpenAI, Gemini, Claude, etc.) and orchestration frameworks such as

LangChain

and

LlamaIndex .

Advanced skills in

prompt engineering

and

context engineering , including familiarity with prompt design tools/frameworks and dynamic context orchestration.

Proficiency with

vector databases

and embedding models for large‑scale retrieval.

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.

Experience working with AWS (or equivalent) cloud infrastructure for AI/GenAI.

Experience with containerization ( Docker ), orchestration ( Kubernetes ), and CI/CD pipelines for AI/agentic applications.

Strong skills in

NLP

(NER, dependency parsing, text classification, topic modeling).

Solid understanding of AI compliance, guardrails, and responsible AI practices.

Demonstrated portfolio of successful AI‑driven projects in a business environment.

Required Soft Skills

Robust 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.

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

Primary Location Full Time Salary Range: $120,800.00 - $170,800.00

Most Relevant Skills Please see the requirements listed above.

Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.

Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate’s skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

This job opening is for an existing job vacancy.

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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📌 Senior Agentic AI Engineer (Mississauga)
🏢 Citigroup
📍 Mississauga