A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio
In this role you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers) where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
- As a Software Developer you'll participate in many aspects of the software development lifecycle such as design code implementation testing and support. You will create software that enables your clients' hybrid-cloud and AI journeys.
- Your primary responsibilities include:
- Comprehensive Feature Development and Issue Resolution: Working on the end to end feature development and solving challenges faced in the implementation.
- Stakeholder Collaboration and Issue Resolution: Collaborate with key stakeholders internal and external to understand the problems issues with the product and features and solve the issues as per SLAs defined. Continuous Learning and Technology Integration: Being eager to learn new technologies and implementing the same in feature development
Responsibilities: Design implement and maintain Python backend services that support agent workflows tool integrations memory systems and context management Develop APIs and microservices enabling communication between AI agents external systems vector databases and orchestration layers Ensure scalability security and performance of backend components running in cloud-native environments (Kubernetes serverless containers) Integrate AI/LLM components with backend logic including retrieval pipelines agent orchestration frameworks and evaluation or guardrail modules Collaborate with AI engineers DevOps and product teams to deliver high-quality production-grade Agentic AI capabilities with CI/CD and observability in place
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