Bloomberg Law is transforming the legal industry through AI-powered products that help legal professionals research, analyze, draft, and make decisions faster. Our mission is to provide the foundational AI platform that enables teams across Bloomberg Law to build and deploy innovative AI solutions while maintaining the reliability, compliance, and scale expected of Bloomberg products.

The Senior Software Engineer will be part of the AI Platform Engineering group within Bloomberg Law, responsible for developing and operating the cloud-native platforms, APIs, developer tooling, and infrastructure that power AI products across Legal, Tax, Government, and other business units. The team focuses on building self-service platforms, agent-ready infrastructure, and developer experiences that accelerate AI product development while abstracting the complexity of underlying model providers and cloud environments.

As a Senior Software Engineer on the AI Platform Engineering team, your mission is to design and build reliable, scalable, and model-agnostic platforms that enable engineers to rapidly develop, deploy, and operate AI-powered applications. Our culture of intellectual curiosity, technical excellence, ownership, and adaptability allows us to stay at the forefront of a rapidly evolving AI landscape. A successful candidate will be self-motivated, highly collaborative, comfortable with ambiguity, and excited to solve complex engineering challenges.

Legal AI is one of the most exciting and fast-moving areas in technology today. If you are interested in building the foundational platforms that power the next generation of AI products, we'd love to hear from you.

We'll trust you to:

• Design and build scalable platform services, APIs, and developer tooling that support AI applications across Bloomberg Law.



• Develop and maintain high-throughput systems that serve millions of requests and power mission-critical AI products.


• Build and extend internal AI and agent platforms, including tool orchestration, execution environments, workflow automation, and agent-ready infrastructure.


• Partner closely with software engineers, AI engineers, and product teams to accelerate the development and deployment of AI-powered products.


• Design and implement model-agnostic platform capabilities that enable seamless integration with providers such as OpenAI, Anthropic, Gemini, AWS Bedrock, and future platforms.


• Build and maintain cloud infrastructure using Infrastructure as Code (Terraform) and modern software engineering practices.


• Develop self-service tooling, frameworks, templates, and workflows that improve developer productivity and reduce operational overhead.


• Improve platform reliability, observability, security, and scalability through modern cloud-native engineering practices.



• Evaluate emerging AI technologies and adapt platform capabilities to support new workflows and development patterns.

  
  

You'll need to have:

• 6+ years of professional software engineering experience.



• Strong proficiency in Python and experience building production-grade backend services and APIs.


• Experience designing, building, and operating distributed systems in cloud environments.


• Experience developing applications on AWS and familiarity with core cloud services such as EC2, S3, IAM, and container-based workloads.


• Hands-on experience with Infrastructure as Code, preferably Terraform.


• Strong understanding of software architecture, databases, networking, cloud infrastructure, and modern application development patterns.


• Experience building and shipping production software as part of a full-stack or backend-focused engineering team.



• A degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

  
  

We'd love to see:

• Experience building internal developer platforms, platform-as-a-service (PaaS) solutions, or engineering productivity tooling.



• Experience building full-stack applications and developer-facing products.


• Familiarity with Kubernetes, Docker, container orchestration, and cloud-native development patterns.


• Experience with observability, monitoring, OpenTelemetry, and production operations.


• Experience building AI-powered applications and agent-based systems.


• Understanding of agent architectures, tool calling, workflow orchestration, and multi-step AI systems.


• Familiarity with modern AI development workflows and tools


• Experience with model deployment, inference systems, AI serving platforms, or AI infrastructure.


• Familiarity with SageMaker, Bedrock, or other managed AI platforms.


• Working knowledge of machine learning concepts and the ML development lifecycle.



• Curiosity to new technologies and adapt quickly in a rapidly evolving technical landscape.