Lead Software Engineer - AI

JPMorgan Chase JPMorgan Chase · Banking · Dublin, Ireland · Corporate Sector

Lead Software Engineer role focused on building AI-powered automation and IoT solutions, integrating LLM capabilities into business workflows and smart building systems. Requires strong full-stack development, system design, and experience with LLMs, generative AI use cases (RAG, agents, orchestration, evaluation/guardrails), and cloud-native microservices.

What you'd actually do

  1. Lead the creation and implementation of AI-driven capabilities, including LLM-based services, orchestration, and integrations into business workflows.
  2. Build and evolve IoT platform integrations (device telemetry, commands, events, device onboarding/management) for Smart Building and Workplace systems.
  3. Architect and deliver cloud-native microservices and APIs (REST/streaming), ensuring scalability, resilience, and strong security controls.
  4. Write secure, high-quality production code; review, mentor, and unblock other engineers through code reviews and technical leadership.
  5. Identify and automate solutions for recurring operational issues to improve system stability and observability (logs/metrics/tracing).

Skills

Required

  • Formal training or certification in software engineering with 6+ years of professional experience.
  • Strong system design, application development, and operational stability skills in production environments.
  • Advanced Java proficiency
  • Hands-on experience with Large Language Models (LLMs) and generative AI use cases (e.g., RAG, agents, prompt/tool orchestration, evaluation/guardrails).
  • Familiarity with AI/ML frameworks and ecosystems such as PyTorch, TensorFlow, scikit-learn, Hugging Face.
  • Experience with distributed systems and at least one major cloud platform (AWS, GCP, or Azure).
  • Expertise in microservices, RESTful APIs, and data technologies (relational and/or NoSQL).
  • Familiarity with Docker, Kubernetes, Helm, and modern CI/CD practices.
  • Strong communication skills and a proactive approach to continuous improvement.
  • Deep understanding of IoT architectures, protocols, device management patterns, and security best practices.
  • Experience integrating IoT solutions within smart building systems / property management platforms, including cloud integration and edge computing patterns.
  • Track record delivering scalable, reliable, and secure products from concept to launch.

Nice to have

  • working knowledge of Python (for AI/ML integrations)
  • Cloud certification in AWS, GCP, or Azure.
  • Practical experience building cloud-native systems (event-driven architectures, streaming, service mesh, etc.).
  • Familiarity with Spark, distributed computing, and platforms such as Databricks.

What the JD emphasized

  • Lead the creation and implementation of AI-driven capabilities, including LLM-based services, orchestration, and integrations into business workflows.
  • Hands-on experience with Large Language Models (LLMs) and generative AI use cases (e.g., RAG, agents, prompt/tool orchestration, evaluation/guardrails).
  • Deep understanding of IoT architectures, protocols, device management patterns, and security best practices.
  • Track record delivering scalable, reliable, and secure products from concept to launch.

Other signals

  • Generative AI/LLM capabilities
  • LLM-based services, orchestration
  • Hands-on experience with Large Language Models (LLMs) and generative AI use cases