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Citi

Senior Lead, GenAI Tech

Citi

. Execute the delivery roadmap for generative and agentic AI projects, aligning work with business objectives and timelines .

Posted 9/24/2026full-timeUnited StatesSenior💰 $141,440 - $212,160 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in managing the full project lifecycle for generative and agentic AI projects, with a strong focus on team leadership, stakeholder communication, and the implementation of ethical AI frameworks. Proficient in advanced AI/ML techniques, cloud infrastructure, and agile methodologies to ensure successful delivery of scalable AI solutions.

Highest-signal resume keywords
Generative AI ExpertiseProject ManagementTeam LeadershipAWS Services ProficiencyAgile/Scrum Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
AI/ML ExperienceAdvanced Context EngineeringPrompt EngineeringNLP SkillsData PreprocessingDockerKubernetesCI/CD PipelinesAgentic AIMulti-Agent Orchestration
Soft Skills
Stakeholder ManagementCommunication AbilitiesRisk Management
Tools & Technologies
Google Agent Development KitLangGraphMicrosoft Agent FrameworkOpenAI Agents SDKHugging FaceGitOpenTelemetry
Industry Keywords
Ethical AI FrameworksAI ComplianceData PrivacyAgent IsolationMLOps

Tech Stack

Tools & technologies
AWSCloudDockerKubernetes

About the role

Key responsibilities & impact
  • Execute the delivery roadmap for generative and agentic AI projects, aligning work with business objectives and timelines
  • Manage project lifecycles from ideation and scoping through deployment and post-launch support
  • Build, mentor, and manage a high-performing team of AI engineers and specialists
  • Oversee design, development, and deployment of robust, scalable, production-ready GenAI and agentic applications
  • Drive design and delivery of agentic workflows and multi-agent systems
  • Establish standards for agent harnesses, orchestration patterns, and reliable long-running agent execution
  • Manage stakeholder expectations, communicate project progress, identify and mitigate risks, and ensure on-time, on-budget delivery
  • Collaborate with Data Mesh, Cloud Architecture, MLOps/LLMOps, and business unit teams
  • Drive adoption of software development, CI/CD, LLMOps, agent observability, Agile/Scrum, and project management best practices
  • Implement governance and ethical AI frameworks, including guardrails, agent isolation/sandboxing, responsible AI practices, data privacy, and corporate policy compliance

Requirements

What you’ll need
  • Bachelor’s or Master’s degree in computer science, Data Science, AI, or a related field
  • 10+ years of overall experience
  • 6+ years of experience in AI/ML, with at least 3 years in Generative AI, including agentic AI
  • Extensive hands-on experience with AWS services and infrastructure related to AI/GenAI
  • Strong portfolio of projects showcasing successful delivery of AI solutions into a production business environment
  • Deep understanding of foundation models, LLMs, embeddings, tokenization, and context-window management
  • Expertise in advanced context engineering, prompt engineering, RAG, knowledge graphs, Graph RAG, agentic AI, and multi-agent orchestration
  • Experience with Google Agent Development Kit (ADK), LangGraph, Microsoft Agent Framework, CrewAI, OpenAI Agents SDK, and comparable frameworks
  • Strong grasp of harness engineering, agent isolation/sandboxing, MCP, and A2A protocols
  • Working knowledge of ML frameworks and extensive hands-on AWS or equivalent cloud experience
  • Advanced NLP skills, including NER, dependency parsing, text classification, and topic modeling
  • Expertise in Docker, Kubernetes, and CI/CD pipelines for LLMOps
  • Strong proficiency in data preprocessing, document ingestion, large-scale datasets, real-time and streaming AI applications, and RESTful APIs
  • Experience with LangGraph, Autogen, CrewAI, LangChain, LlamaIndex, Hugging Face, Google ADK, OpenAI, Gemini, Claude, and Git
  • Experience with agent observability and evaluation tooling, including OpenTelemetry-based observability
  • Knowledge of AI compliance frameworks and experience implementing guardrails
  • Proven ability to lead and deliver complex, large-scale technical projects from concept to production
  • Expertise in Agile/Scrum, project planning, resource allocation, and risk management
  • Ability to translate AI strategy into an actionable delivery plan
  • Exceptional stakeholder management and communication abilities

Benefits

Comp & perks
  • Hybrid working model with 3 days in the office and 2 days working remotely
  • Continuous learning and professional development opportunities
  • Competitive compensation and comprehensive benefits package
  • Medical, dental & vision coverage
  • 401(k)
  • Life, accident, and disability insurance
  • Wellness programs
  • Paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
  • Discretionary and formulaic incentive and retention awards may be available for eligible employees
  • Wellbeing support and work-life balance resources