We are seeking an experienced and highly skilled Agentic AI Senior Engineer to lead the design, development, and deployment of cutting-edge agentic AI solutions. This role involves significant hands-on development in Python, architecting advanced multi-agent systems, and driving the adoption of generative AI platforms. The ideal candidate will possess deep technical expertise, contribute actively to an Agile team, and foster technical excellence.
Key Responsibilities- Design, develop, and deploy large-scale agentic AI solutions using frameworks like Google ADK, LangChain, and LangGraph.
- Architect and implement multi-agent systems, integrating LLMs (OpenAI, Anthropic, Google Gemini) and AI-powered capabilities (Vertex AI, Google A2UI, RAG pipelines, vector databases).
- Engineer autonomous agents with planning, tool usage, memory management, and multi-step reasoning.
- Develop scalable Python backend services (FastAPI, asyncio) with resilient APIs and microservices.
- Build and maintain robust data pipelines (SQL, NoSQL) and secure REST APIs.
- Drive CI/CD practices, automated testing, MLOps, and containerization (Docker, Kubernetes) on cloud platforms (AWS, Azure, GCP).
- Provide technical guidance, ensure adherence to best practices, and mentor junior engineers.
- Experience: 5+ years in AI/ML development, applications development, or systems analysis, with a substantial focus on Python. Minimum 2+ years specifically in AI, prompt engineering, ML, or agentic AI systems. Proven experience as a lead developer for agentic flow design with Google ADK.
- Technical Skills:
- Python Expertise: Advanced knowledge of Python ecosystem (FastAPI, Django, Flask, asyncio, PySpark) for scalable, resilient applications.
- AI/ML/LLM: Deep expertise in LLMs (OpenAI GPT, Gemini, Claude, Llama), LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI. Exposure to TensorFlow, PyTorch, scikit-learn, and AI coding tools (Copilot, Devin).
- Databases: Experience with relational (PostgreSQL, Oracle, SQL Server) and NoSQL (MongoDB, Cassandra, Redis) databases. Proven experience with RAG systems and vector databases (Pinecone, Weaviate).
- Cloud & DevOps: Strong background in AWS, Azure, GCP, Docker, Kubernetes, CI/CD (Jenkins, GitLab CI, GitHub Actions), and MLOps.
- Software Engineering: Proficiency in secure REST API design, microservices, event-driven architecture, distributed systems, automated testing (Pytest, unittest), and modern version control (Git).
Desirable Qualifications
- Experience with Java development in enterprise contexts.
- Knowledge of modern frontend frameworks (React, Angular, Vue.js).
Education
- Bachelor’s degree in computer science, Engineering, or equivalent experience
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Job Family Group: Technology------------------------------------------------------
Job Family:Applications Development------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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Skills Required
- 5+ years in AI/ML development, applications development, or systems analysis with substantial Python focus
- Minimum 2+ years specifically in AI, prompt engineering, ML, or agentic AI systems
- Proven experience as a lead developer for agentic flow design with Google ADK
- Advanced Python expertise (FastAPI, Django, Flask, asyncio, PySpark) for scalable applications
- Deep expertise with LLMs and agent frameworks (OpenAI GPT, Gemini, Claude, Llama, LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI)
- Experience with ML frameworks and tools (TensorFlow, PyTorch, scikit-learn) and AI coding tools (Copilot, Devin)
- Experience building RAG systems, vector DBs and working with Pinecone or Weaviate
- Database experience (PostgreSQL, Oracle, SQL Server, MongoDB, Cassandra, Redis) and SQL/NoSQL pipelines
- Cloud and DevOps experience (AWS, Azure, GCP, Docker, Kubernetes, CI/CD: Jenkins, GitLab CI, GitHub Actions) and MLOps
- Proficiency in secure REST API design, microservices, event-driven and distributed systems, and automated testing (Pytest, unittest)
- Proven ability to provide technical guidance and mentor junior engineers within Agile teams
- Bachelor's degree in computer science, engineering, or equivalent experience
- Experience with Java development in enterprise contexts
- Knowledge of modern frontend frameworks (React, Angular, Vue.js)
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
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Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
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Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
Citi Insights
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