Senior Software Engineer

Job description

JLL empowers you to shape a brighter way.   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 with deep Python expertise to join our engineering team at JLL Technologies. You will design, develop, and maintain backend services and data platform components that power Azara, our AI-driven data intelligence platform for commercial real estate. This is an individual contributor role with significant technical influence, requiring you to drive architectural decisions, mentor engineers, and deliver production-grade solutions at scale. Key Responsibilities Backend Development & Architecture • Design and develop high-performance backend services and APIs using Python (FastAPI, Django, or Flask) following clean architecture and domain-driven design principles • Build and maintain asynchronous processing pipelines using Celery, Redis, and event-driven microservices (Dapr, Azure Service Bus) for real-time and batch data workflows • Architect scalable microservices that handle high-throughput data ingestion, transformation, and serving for analytics and AI features • Own end-to-end delivery of backend features from design through deployment, including performance tuning and production support Data Platform & Integration • Develop and optimize data pipelines integrating with Databricks, SQL databases, and cloud-native storage services • Design and implement caching strategies, data access layers, and API contracts that serve both internal services and external consumers • Collaborate with data engineering and data science teams to operationalize ML models and analytics workflows • Integrate with third-party APIs and enterprise systems, ensuring reliability, idempotency, and fault tolerance Quality & Engineering Excellence • Lead code reviews, establish coding standards, and champion engineering best practices across the team • Design comprehensive testing strategies including unit, integration, and contract testing • Implement observability and monitoring using Datadog, OpenTelemetry (distributed tracing), and structured logging • Drive adoption of CI/CD best practices, automated testing, and infrastructure-as-code in the development workflow AI Augmentation & Agent Development • Leverage AI-powered development tools (Cursor AI, GitHub Copilot) across all phases of the SDLC — from code generation and reviews to testing and documentation • Design and develop AI agents and intelligent automation for backend and data workflows (e.g., data pipeline automation agents, testing agents, code review agents) • Identify opportunities to integrate AI capabilities into existing services and engineering processes Mentorship & Collaboration • Mentor junior and mid-level engineers on Python best practices, design patterns, and architectural thinking • Collaborate with cross-functional teams including product managers, UX designers, and DevOps engineers • Contribute to technical documentation, HLDs/LLDs, and architectural decision records • Participate in Agile ceremonies, sprint planning, and estimation activities Required Qualifications • Deep hands-on experience with at least one Python web framework (FastAPI, Django, or Flask) and Pydantic for data validation • Strong experience with asynchronous task processing (Celery, Redis) and event-driven architectures (Dapr, Azure Service Bus) • Proficiency in SQL and relational databases (PostgreSQL, SQL Server) and database migration tools (Alembic) • Solid understanding of RESTful API design, microservices architecture, and distributed systems • Experience with Microsoft Azure cloud platform (App Services, Functions, Storage, Key Vault, Data Lake) • Proficiency with Git, CI/CD pipelines, and modern development workflows • Proficiency with AI-powered development tools (Cursor AI, GitHub Copilot, or similar) for AI-augmented software development across the SDLC • Demonstrated ability to design and develop AI agents or intelligent automation solutions for backend and data engineering workflows • Strong understanding of software design patterns, SOLID principles, and clean code practices Preferred Qualifications • Experience with Databricks for data engineering and analytics • Familiarity with containerization (Docker) and orchestration (Kubernetes) • Experience with OpenTelemetry for distributed tracing and observability • Knowledge of feature management platforms (LaunchDarkly or similar) • Experience with event-driven autoscaling (KEDA) and multi-tenant architecture patterns • Exposure to LLM integration, RAG pipelines, or agent orchestration frameworks (LangChain, LangGraph) • Experience with Infrastructure as Code (Terraform, Bicep) <