
Citi
New York, New York • Today
Full-time
Compensation information provided in the description
5850 results (330 new)

Citi
New York, New York • Today
Full-time
Compensation information provided in the description

TECHNEPTUNE CONSULTING INC
Paramus, New Jersey • Today
Easy Apply
Full-time
Depends on Experience

Factspan Inc
Hybrid in Atlanta, Georgia • 12d ago
Easy Apply
Full-time
Depends on Experience

LaSalle Network
Chicago, Illinois • Today
Easy Apply
Full-time
$170000.00 - $300000.00 per annum

Arrowminds inc
Irvine, California • 4d ago
Easy Apply
Full-time, Part-time, Third Party, Contract

Mitchell Martin, Inc.
Hybrid in Toronto, Ontario • 13d ago
Easy Apply
Full-time, Third Party
$16625 - $23750

Mitchell Martin, Inc.
Hybrid in Toronto, Ontario • 13d ago
Easy Apply
Contract, Third Party
$67.375 - $96.25

Mitchell Martin, Inc.
Remote • 27d ago
Easy Apply
Full-time, Third Party
$129500 - $185000

New York Technology Partners
Remote • Today
Easy Apply
Full-time
Depends on Experience

Charter Global, Inc.
Hybrid in New York, New York • Yesterday
Easy Apply
Third Party, Contract
$70 - $80

Aptino
Miami, Florida • 22d ago
Easy Apply
Third Party, Contract
Depends on Experience

Cyma Systems Inc
Dallas, Texas • 20d ago
Easy Apply
Contract
Depends on Experience

Galaxy i Technologies, Inc.
San Jose, California • Today
Contract, Third Party
Depends on Experience

Lorven Technologies, Inc.
Cleveland, Ohio • 7d ago
Easy Apply
Full-time, Third Party
$120000 - $130000

Capital One
New York, New York • Today
Full-time

Capital One
Richmond, Virginia • Today
Full-time

Capital One
McLean, Virginia • Today
Full-time
Job Summary/Position Overview
We are seeking a highly skilled and pragmatic AI Lead to design, develop, and deploy advanced AI solutions. This multifaceted role involves creating intelligent AI agents capable of understanding goals, planning actions, and executing tasks with minimal human intervention, as well as contributing to the development and implementation of generative AI solutions. The ideal candidate will possess a strong understanding of AI principles, agent-based systems, machine learning, software engineering and management best practices. This hybrid position emphasizes technical leadership, focusing on rapid prototyping, iterative improvement, and delivering measurable business value by translating research ideas into robust, scalable production systems.
Agent and Generative AI Development: Design, implement, and deploy intelligent agents, including perception, reasoning, planning, and action execution modules. Contribute to the development and implementation of generative AI solutions, ensuring they meet technical requirements and business objectives.
System Architecture & Scalability: Develop scalable and robust architectures for agentic systems and generative AI applications, ensuring high performance, reliability, and security.
Machine Learning & LLM Integration: Integrate various machine learning models (e.g., LLMs, reinforcement learning, predictive models) to enhance agent capabilities and decision-making. Implement LLM integration using platforms like OpenAI, Anthropic, and Bedrock APIs.
Task Automation & Workflow Optimization: Develop agents that can automate complex tasks, optimize workflows, and solve real-world problems across various domains.
Rapid Delivery: MVP first approach, iterative improvement approach with a focus on "time to value" (quick iterations, hypothesis testing, A/B experiments).
Framework and Tooling: Utilize and contribute to agentic AI frameworks and development tools. Build full-stack applications that integrate existing ML/LLM tools and services.
Evaluation and Optimization: Design and implement metrics and evaluation strategies for agent performance, continuously optimizing and improving agent behavior.
Research and Innovation: Stay abreast of the latest advancements in AI, particularly in agent-based systems, autonomous AI, and related fields, and propose innovative solutions. Demonstrate deep expertise in generative AI technologies, actively participating in the development of proofs of concept (POCs) and exploring new methodologies.
Collaboration & Leadership: Work closely with cross-functional teams (AI researchers, data scientists, product managers, software engineers) to integrate agentic and generative AI solutions into broader products and services. Lead technical teams through hands-on coding and architectural decisions, championing pragmatic "buy and integrate" approaches.
Documentation: Create comprehensive technical documentation for agent designs, implementations, and operational procedures.
Education: Bachelor\'s or Master\'s degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
Experience:
10+ years software engineering experience with recent hands-on coding, with a track record of rapid delivery and launching multiple AI features in production.
Minimum 3+ years of professional experience in software development with a focus on AI, prompt engineering, machine learning and/or agentic AI systems.
Experience in the finance industry is a plus.
Programming Proficiency:
Strong proficiency in Python (FastAPI, Django, Flask, PySpark) or Java (Spring Boot, Spring Cloud, Spring Security), and SQL.
JavaScript (React, Next.js, Node.js, TypeScript).
Full-stack development with a focus on rapid prototyping.
AI/ML Expertise:
Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems.
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas).
Familiarity with large language models (LLMs) like ChatGPT, LaMDA/Gemini, Llama, etc., and their application in agentic systems.
Familiarity with specific agent frameworks (e.g., LangChain, AutoGen, CrewAI, RAG) or research in multi-agent reinforcement learning.
Experience in designing and implementing APIs for AI services.
Software Engineering: Experience with software development best practices, including version control (Git), CI/CD pipelines, testing, and code reviews. Understanding of agile methodologies, application resiliency, and security applied to AI projects. Proven experience in system design, application development, and operational stability in AI projects.
Application and Data Architecture: Experience with application and data architecture patterns and designs. Thorough understanding of data flows from producer to consumer systems. Familiarity with data engineering practices to support AI model training and deployment. Leveraging managed services and existing platforms, with an API-First Design emphasizing microservices and event-driven architectures.
Containerization: Experience with Docker and Kubernetes.
Problem-Solving: Excellent analytical and problem-solving skills with a creative approach to complex challenges.
Communication: Strong written and verbal communication skills, with the ability to articulate complex technical concepts to diverse audiences.
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In addition to salary, Citi?s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
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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 .
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