Citi is looking for a senior Python and Data Engineer with deep, hands-on experience in Agentic AI to help build the next generation of intelligent, autonomous systems at the core of our technology transformation. In this role, you will design, engineer, and operate production-grade Agentic AI platforms that combine advanced reasoning, planning, memory, and action with robust data engineering foundations. You will work closely with AI scientists, platform architects, and product teams to translate complex business problems into scalable systems that think, decide, and act with minimal human intervention.
Responsibilities
- Design and deliver end-to-end Agentic AI and data engineering solutions, spanning architecture, system design, and high-quality, production-grade Python development.
- Engineer autonomous AI agents and multi-agent systems using LLMs and agent frameworks, incorporating planning, tool usage, memory, and multi-step reasoning patterns.
- Build AI-powered capabilities using Google Gemini, Vertex AI, Agent Development Kit (ADK), vector databases, RAG pipelines, semantic search, and advanced prompt and context management techniques.
- Develop scalable, high-performance backend services in Python (e.g., FastAPI, asyncio), implementing resilient APIs, event-driven designs, and microservices architectures.
- Design, build, and maintain robust data pipelines and data models, working with SQL databases (Oracle, PostgreSQL) and NoSQL stores such as MongoDB.
- Implement secure, well-structured REST APIs and agent interfaces, applying strong authentication, authorisation (OAuth, token-based access), and encryption best practices.
- Optimise AI agent performance, latency, and cost through profiling, prompt optimisation, caching strategies, vector index tuning, and distributed system optimisation.
- Drive CI/CD practices integrating automated testing, agent evaluation, code quality gates, containerisation, and cloud-native deployment pipelines.
- Partner with quality engineering teams to develop automated test strategies for AI systems, covering agents, APIs, integrations, regression, and performance scenarios.
- Diagnose and resolve production issues across AI agents, data pipelines, and services using strong observability and root cause analysis practices.
- Mentor and share knowledge across the engineering organisation through design reviews, technical forums, and continuous learning initiatives.
Required qualifications & skills
- 10+ years of experience in software engineering or product development environments.
- Expert-level, hands-on Python engineering experience, with strong fundamentals in algorithms, data structures, concurrency, and software design patterns.
- Proven experience building Agentic AI solutions, including autonomous agents, multi-agent orchestration, tool-calling, memory management, and LLM-based reasoning workflows.
- Strong practical experience with Python AI and data libraries, such as LangChain, LlamaIndex, Pydantic, NumPy, Pandas, SQLAlchemy, and vector database SDKs.
- Solid data engineering expertise, including SQL (Oracle, PostgreSQL), NoSQL (MongoDB), and scalable data ingestion and transformation pipelines.
- Experience delivering complex systems using agile methodologies, with the ability to operate independently across the full development lifecycle.
- Strong analytical, problem-solving, and quantitative skills with a pragmatic, results-driven mindset.
- Excellent written and verbal communication skills, with the ability to collaborate effectively across engineering, AI, and product teams.
- Bachelor’s degree or equivalent practical experience in computer science, engineering, or a related field.
Beneficial skills & qualifications
- Experience with agent evaluation frameworks, prompt benchmarking, and AI system observability.
- Familiarity with GraphQL APIs, event streaming platforms, and advanced integration patterns.
- Exposure to cloud-native AI and data platforms, including containers, orchestration, and infrastructure as code.
- Understanding of security, compliance, and risk considerations for deploying AI systems in regulated environments.
- Industry certifications in cloud, AI engineering, or data engineering disciplines.
What we offer
- The opportunity to build cutting-edge Agentic AI systems solving meaningful, large-scale problems within a global financial institution.
- A hybrid working model supporting in-office collaboration and flexible work arrangements.
- Access to professional development resources, continuous learning programmes, and career growth opportunities.
- A culture that values innovation, employee wellbeing, and healthy work-life balance.
- Parental, family, and retirement support as part of Citi’s comprehensive employee offering.
If you have a passion for Agentic AI, deep Python expertise, and strong data engineering foundations, we encourage you to apply and help shape the future of intelligent systems at Citi.
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Job Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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