{"schemaVersion":"jobsearcher.job.v1","id":"10a6aa93a1edf5b406a25feb","url":"https://jobsearcher.com/jobs/10a6aa93a1edf5b406a25feb","canonicalUrl":"https://jobsearcher.com/jobs/10a6aa93a1edf5b406a25feb","title":"VP, Applications Development – Tech Lead (Java, UI, PL-SQL & Agentic AI)","description":"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.\n\nKey Responsibilities\nCollaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges.\nArchitect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production.\nDesign and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG).\nBuild and optimize RAG systems, including hybrid search, multi-vector retrieval, and re-ranking pipelines.\nDesign and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains.\nArchitect 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.\nDesign robust agent harnesses — governance, constraints, feedback loops, state/session management, and execution controls that make long-running agent systems reliable and safe.\nIntegrate agents with tools and data via the Model Context Protocol (MCP) and orchestrate inter-agent collaboration and task delegation via the Agent2Agent (A2A) protocol.\nSupport the integration of GenAI and agentic applications into production environments, ensuring robust deployment, scalability, observability, and maintainability.\nContribute to the development and optimization of real-time and streaming AI solutions.\nStay current with the latest advances in generative and agentic AI and actively share knowledge with the team.\nEnsure adherence to ethical AI guidelines, guardrails, agent isolation/sandboxing, data privacy, and compliance standards.\nMentor junior team members, provide code reviews, and foster a culture of technical excellence.\nRequired Technical Skills\nDeep, hands-on expertise in core generative AI concepts — foundation models, LLMs, embeddings, tokenization, and context-window management.\nAdvanced skills in prompt engineering and context engineering, including familiarity with prompt design tools/frameworks and dynamic context orchestration.\nStrong experience building RAG systems, including chunking strategies, hybrid search, and multi-vector retrieval.\nPractical experience designing knowledge graphs and Graph RAG pipelines (e.g., using graph databases such as Neo4j or ArangoDB) for relationship-aware, multi-hop retrieval.\nProven 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.\nStrong grasp of multi-agent orchestration patterns (supervisor/worker, hierarchical, peer-to-peer) and harness engineering (governance, feedback loops, execution controls, agent isolation/sandboxing).\nHands-on experience with agent interoperability protocols — the Model Context Protocol (MCP) for tool/data access and the Agent2Agent (A2A) protocol for inter-agent collaboration.\nExperience with agent observability and evaluation (e.g., tracing, OpenTelemetry-based tooling) for production agent systems.\nProficiency with major GenAI APIs (OpenAI, Gemini, Claude, etc.) and orchestration frameworks such as LangChain and LlamaIndex.\nStrong skills in NLP (NER, dependency parsing, text classification, topic modeling).\nProficiency with vector databases and embedding models for large-scale retrieval.\nExperience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI/agentic applications.\nSolid understanding of AI compliance, guardrails, and responsible AI practices.\nStrong skills in Python and experience with data preprocessing, document ingestion, and API development.\nRequired Soft Skills\nStrong collaboration skills to work effectively in cross-functional teams.\nAnalytical and proactive approach to problem-solving.\nClear communication skills for both technical and non-technical audiences.\nEagerness to learn, innovate, and mentor less experienced developers.\nQualifications\nBachelor's or master's degree in Computer Science, Data Science, AI, or a related field.\n5–7 years of experience in AI/software development, including significant experience in Generative AI and agentic AI.\nDemonstrated portfolio of successful AI-driven projects in a business environment.\nExperience working with AWS (or equivalent) cloud infrastructure for AI/GenAI.\n\n#LI-DD2\n\n-\n\nJob Family Group:\nTechnology\n\n-\n\nJob Family:\nApplications Development\n\n-\n\nTime Type:\nFull time\n\n-\n\nPrimary Location:\nTampa Florida United States\n\n-\n\nPrimary Location Full Time Salary Range:\n$113,840.00 - $170,760.00\n\nIn 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.\n\n-\n\nMost Relevant Skills\nPlease see the requirements listed above.\n\n-\n\nOther Relevant Skills\nFor complementary skills, please see above and/or contact the recruiter.\n\n-\n\nAnticipated Posting Close Date:\nSep 01, 2026\n\n-\n\nAutomated Processing and AI\n\nWe 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.\n\nImportantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.\n\nIllinois residents – AI Notice and Right\n\n-\n\nCiti 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.\n\nIf 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.\n\nView Citi’s EEO Policy Statement and the Know Your Rights poster.","company":"Citi","rawCompany":"citi","city":"Tampa","state":"FL","isRemote":false,"isActive":false,"createdAt":"2026-09-02T10:43:54.082Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"VP, Applications Development – Tech Lead (Java, UI, PL-SQL & Agentic AI)","description":"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.\n\nKey Responsibilities\nCollaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges.\nArchitect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production.\nDesign and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG).\nBuild and optimize RAG systems, including hybrid search, multi-vector retrieval, and re-ranking pipelines.\nDesign and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains.\nArchitect 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.\nDesign robust agent harnesses — governance, constraints, feedback loops, state/session management, and execution controls that make long-running agent systems reliable and safe.\nIntegrate agents with tools and data via the Model Context Protocol (MCP) and orchestrate inter-agent collaboration and task delegation via the Agent2Agent (A2A) protocol.\nSupport the integration of GenAI and agentic applications into production environments, ensuring robust deployment, scalability, observability, and maintainability.\nContribute to the development and optimization of real-time and streaming AI solutions.\nStay current with the latest advances in generative and agentic AI and actively share knowledge with the team.\nEnsure adherence to ethical AI guidelines, guardrails, agent isolation/sandboxing, data privacy, and compliance standards.\nMentor junior team members, provide code reviews, and foster a culture of technical excellence.\nRequired Technical Skills\nDeep, hands-on expertise in core generative AI concepts — foundation models, LLMs, embeddings, tokenization, and context-window management.\nAdvanced skills in prompt engineering and context engineering, including familiarity with prompt design tools/frameworks and dynamic context orchestration.\nStrong experience building RAG systems, including chunking strategies, hybrid search, and multi-vector retrieval.\nPractical experience designing knowledge graphs and Graph RAG pipelines (e.g., using graph databases such as Neo4j or ArangoDB) for relationship-aware, multi-hop retrieval.\nProven 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.\nStrong grasp of multi-agent orchestration patterns (supervisor/worker, hierarchical, peer-to-peer) and harness engineering (governance, feedback loops, execution controls, agent isolation/sandboxing).\nHands-on experience with agent interoperability protocols — the Model Context Protocol (MCP) for tool/data access and the Agent2Agent (A2A) protocol for inter-agent collaboration.\nExperience with agent observability and evaluation (e.g., tracing, OpenTelemetry-based tooling) for production agent systems.\nProficiency with major GenAI APIs (OpenAI, Gemini, Claude, etc.) and orchestration frameworks such as LangChain and LlamaIndex.\nStrong skills in NLP (NER, dependency parsing, text classification, topic modeling).\nProficiency with vector databases and embedding models for large-scale retrieval.\nExperience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI/agentic applications.\nSolid understanding of AI compliance, guardrails, and responsible AI practices.\nStrong skills in Python and experience with data preprocessing, document ingestion, and API development.\nRequired Soft Skills\nStrong collaboration skills to work effectively in cross-functional teams.\nAnalytical and proactive approach to problem-solving.\nClear communication skills for both technical and non-technical audiences.\nEagerness to learn, innovate, and mentor less experienced developers.\nQualifications\nBachelor's or master's degree in Computer Science, Data Science, AI, or a related field.\n5–7 years of experience in AI/software development, including significant experience in Generative AI and agentic AI.\nDemonstrated portfolio of successful AI-driven projects in a business environment.\nExperience working with AWS (or equivalent) cloud infrastructure for AI/GenAI.\n\n#LI-DD2\n\n-\n\nJob Family Group:\nTechnology\n\n-\n\nJob Family:\nApplications Development\n\n-\n\nTime Type:\nFull time\n\n-\n\nPrimary Location:\nTampa Florida United States\n\n-\n\nPrimary Location Full Time Salary Range:\n$113,840.00 - $170,760.00\n\nIn 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.\n\n-\n\nMost Relevant Skills\nPlease see the requirements listed above.\n\n-\n\nOther Relevant Skills\nFor complementary skills, please see above and/or contact the recruiter.\n\n-\n\nAnticipated Posting Close Date:\nSep 01, 2026\n\n-\n\nAutomated Processing and AI\n\nWe 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.\n\nImportantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.\n\nIllinois residents – AI Notice and Right\n\n-\n\nCiti 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.\n\nIf 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.\n\nView Citi’s EEO Policy Statement and the Know Your Rights poster.","datePosted":"2026-09-02T10:43:54.082Z","dateModified":"2026-09-02T10:43:54.082Z","hiringOrganization":{"@type":"Organization","name":"Citi","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Tampa","addressRegion":"FL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"10a6aa93a1edf5b406a25feb"},"url":"https://jobsearcher.com/jobs/10a6aa93a1edf5b406a25feb"}}