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Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong.  Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward.   

About the Role

We are seeking an experienced Senior Software Engineer specialising in Agentic AI to join our Innovation engineering team at JLL Technologies. You will design, build, and deploy production-grade multi-agent AI systems that power next-generation intelligent features within Azara, our AI-driven data intelligence platform for commercial real estate. This role sits at the intersection of software engineering and applied AI, requiring you to architect autonomous agent workflows, build RAG pipelines, orchestrate LLM interactions, and deliver AI solutions that create tangible business value at enterprise scale.

Key Responsibilities

Agentic AI Architecture & Development

• Design and build production-grade multi-agent systems using LangGraph as the primary orchestration framework, with knowledge of LangChain, CrewAI, and AutoGen

• Architect agent orchestration patterns including planning, tool use, persistent state management, memory, reflection, and multi-agent coordination

• Develop and optimize RAG (Retrieval-Augmented Generation) pipelines with document processing, chunking strategies, embedding workflows, and vector database integration

• Build robust agent evaluation, testing, and observability frameworks to ensure reliability and performance in production

• Design natural language to data query solutions integrating with platforms such as Databricks Genie

LLM Integration & Optimization

• Integrate and manage LLM/SLM services (OpenAI, Azure OpenAI, Anthropic, open-source models) with appropriate model selection, prompt engineering, and cost optimization

• Design prompt engineering strategies including chain-of-thought, few-shot, and structured output techniques for reliable agent behavior

• Implement guardrails, safety mechanisms, and content filtering for AI-generated outputs

• Evaluate and benchmark models for latency, accuracy, cost, and domain-specific performance

Platform & Backend Engineering

• Build scalable Python backend services (FastAPI) that serve AI agent workflows to production applications at enterprise scale

• Design and implement caching, rate limiting, persistent agent state, and conversation memory strategies

• Develop event-driven microservices and real-time streaming for AI agent interactions

• Develop APIs and integration layers that connect AI agents with enterprise data sources, tools, and external services

• Implement distributed task processing (Celery) and event-driven autoscaling (KEDA) for production AI workloads

Innovation & Technical Leadership

• Stay current with the rapidly evolving Agentic AI landscape and evaluate emerging frameworks, models, and techniques

• Lead proof-of-concept development for new AI capabilities, moving successful experiments to production

• Mentor engineers on AI engineering best practices, prompt engineering, and agent design patterns

• Contribute to technical documentation, architecture decision records, and AI solution design specifications

• Champion the adoption of AI-powered development tools (Cursor AI, GitHub Copilot) across engineering teams

Required Qualifications

• Strong proficiency in Python with hands-on experience building production AI applications

• Demonstrated experience with LangGraph or similar agentic AI frameworks (LangChain, CrewAI, AutoGen) for production systems

• Hands-on experience with LLM API integration (OpenAI, Azure OpenAI, Anthropic) and prompt engineering

• Experience designing and implementing RAG systems including embedding models, vector databases, and retrieval strategies

• Solid understanding of multi-agent system design, agent orchestration, persistent state management, and memory patterns

• Experience with Python web frameworks (FastAPI) and distributed task processing (Celery) for production APIs

• Experience with event-driven microservices (Dapr) and real-time streaming patterns (SSE)

• Proficiency with AI-powered development tools (Cursor AI, GitHub Copilot, or similar) for AI-augmented software development across the SDLC

• Proficiency with Git, CI/CD pipelines, and cloud platforms (preferably Azure)

Preferred Qualifications

• Experience with vector databases (Qdrant, Pinecone, PgVector, ChromaDB)

• Experience with Databricks Genie or similar natural language to data query platforms

• Experience with AWS Bedrock AgentCore for managed agent runtime and multi-cloud agent deployment

• Experience with multi-tenant architecture patterns and enterprise-scale AI systems

• Experience with containerization (Docker, Kubernetes) and event-driven autoscaling (KEDA)

• Understanding of AI safety, responsible AI principles, and enterprise governance requirements

Technical Skills & Competencies

AI & Agentic Systems

• Primary Framework: LangGraph (multi-agent orchestration with persistent state)

• Additional Frameworks: LangChain, CrewAI, AutoGen

• LLM Providers: OpenAI (GPT-5.x), Azure OpenAI, Anthropic (Claude), enterprise LLM services

• Techniques: RAG, prompt engineering, chain-of-thought, function calling, structured outputs

• Data Intelligence: Databricks Genie (natural language to SQL)

• Vector Databases: Qdrant, Pinecone, Weaviate, ChromaDB

• Multi-Cloud: AWS Bedrock AgentCore (managed agent runtime)

• Patterns: Multi-agent orchestration, tool use, persistent state, memory management, agent evaluation

Core Engineering

• Languages: Python (primary), SQL

• Frameworks: FastAPI, Celery, Pydantic

• Databases: PostgreSQL (multi-tenant), Redis (caching, rate limiting)

• Event-Driven: Dapr, SSE (real-time streaming)

• Patterns: Microservices, event-driven architecture, distributed task processing

Experience & Education

• Bachelor's degree in Computer Science, Engineering, AI/ML, or a related technical field, or equivalent professional experience

• 6+ years of proven software engineering experience with significant hands-on AI/ML work in enterprise environments

• Strong communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders

• Strong knowledge of Agile methodologies and principles

• Demonstrated passion for staying current with the rapidly evolving AI landscape

What We Can Do for You

At JLL, we make sure that you become the best version of yourself by helping you realise your full potential in an entrepreneurial and inclusive work environment. If you have a passion for learning and adopting new technologies, JLL will continuously provide you with platforms to enrich your technical expertise. We will empower your ambitions through our dedicated Total Rewards Program, competitive pay, and benefits package.

Location:

Scheduled Weekly Hours:

If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements.  We’re interested in getting to know you and what you bring to the table!

At JLL, we harness the power of artificial intelligence (AI) to efficiently accelerate meaningful connections between candidates and opportunities. Using AI capabilities, we analyze your application for relevant skills, experiences, and qualifications to generate valuable insights about how your unique profile aligns with the specific requirements of the role you're pursuing.

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