Find your next role
Discover amazing opportunities across our network of companies committed to gender equality in the workplace.
Introduction
At IBM Software, we transform client challenges into solutions. Building the world’s leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You’ll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM’s product and technology landscape. Here, you’ll have the tools and opportunities to advance your career while creating software that changes the world.
Your role and responsibilities
- Design, build, and operate production-grade Python backend services using FastAPI, Pydantic, and Uvicorn (ASGI architecture) with a focus on low-latency, high-reliability systems.
- Own services end-to-end in production, including architecture design, implementation, testing with pytest, deployment, monitoring, and incident response.
- Design API contracts and service boundaries for distributed systems, ensuring clear data flow, backward compatibility, and scalable integration patterns.
- Build and operate LLM and agent-based production systems, integrating frameworks such as LangChain/LangGraph and model providers (e.g., AWS Bedrock, LiteLLM) into real workflows.
- Distinguish and maintain separation between experimentation and production AI systems, ensuring safe rollout of model-driven features.
- Design and evolve CI/CD pipelines that enforce automated testing, security validation, and deterministic, rollback-safe deployments.
- Debug and resolve production incidents in distributed systems using logs, metrics, and distributed tracing (OpenTelemetry / ddtrace patterns), with clear ownership of service health.
- Operate cloud-native services on AWS, including secure configuration, secrets management, IAM-controlled access, and production runtime reliability.
- Design and maintain containerized workloads using Docker and Kubernetes, including rollout strategies (blue/green or rolling), health checks, autoscaling, and resource tuning.
- Build systems with observability standards (metrics, tracing, logging) to ensure measurable reliability, performance, and failure diagnosis.
- Participate in on-call or production support rotation with ownership for service-level outcomes and incident resolution.
- Collaborate in Agile teams to translate stakeholder requirements into production systems, with emphasis on technical design ownership and delivery accountability.
Required education
None
Preferred education
Bachelor's Degree
Required technical and professional expertise
- Experience leading technical design discussions, influencing architecture decisions, and mentoring engineers on production system design and operations
- Proven experience building and operating production backend services in Python using FastAPI, Pydantic, and ASGI-based architectures.
- Demonstrated ownership of systems in production, including deployment, maintaining CI/CD pipelines with automated testing, release gating, and rollback-safe deployment strategies, monitoring, on-call support, and incident resolution
- Strong experience designing and integrating distributed systems, including API contracts, service boundaries, and data flow between components.
- Experience debugging complex production issues using observability tooling (logs, metrics, distributed tracing such as OpenTelemetry or ddtrace).
- Experience building or integrating LLM-based or AI-driven systems, including orchestration frameworks and external model providers.
- Strong testing and code quality discipline, including use of pytest, linting, and automated quality enforcement in CI pipelines.
Preferred technical and professional experience
- Experience operating LLM-based systems in production, including agent orchestration, tool integration, and safe rollout of model-driven features.
- Experience designing event-driven or asynchronous architectures, including message queues, background processing, and workflow orchestration.
- Experience contributing to or owning internal platforms or developer tooling, improving engineering velocity and system reliability.
- Experience implementing security best practices in production, including least-privilege access, secrets rotation, and secure service-to-service communication.