Apptio, an IBM Company, is seeking a Senior Software Development Engineer to join our growing team building innovative, AI-driven solutions across the FinOps and Technology Business Management (TBM) product suite. In this role, you will work closely with data scientists to design, develop, and scale the engineering infrastructure required to bring machine learning and generative AI capabilities into production across our SaaS platforms.
You will play a key role in shaping the future of intelligent product features—enabling smarter automation, deeper analytics, and better business outcomes for our enterprise customers.
- Collaborate with data scientists to productionize AI/ML models, including orchestration, scaling, monitoring, and API integration
- Design and build high-quality, maintainable software systems that deliver AI/ML-powered features within Apptio’s product suite
- Develop secure and scalable microservices, data pipelines, and back-end components in a cloud-native environment
- Work closely with product managers and UX designers to translate business needs into technical solutions
- Contribute to architectural decisions and code reviews while mentoring junior engineers
- Drive performance, scalability, and reliability best practices across AI-integrated features
- Stay up-to-date with emerging trends in software engineering, cloud technologies, and MLOps
- Demonstrated experience in software development, ideally with experience delivering SaaS or data-driven products
- Proficiency in one or more modern languages such as Java, Python, Go, or TypeScript
- Experience building and deploying RESTful APIs, working with containerized environments (e.g., Docker, Kubernetes)
- Solid understanding of cloud platforms (AWS, Azure, or GCP) and CI/CD pipelines
- Demonstrated experience collaborating with data science or ML teams to operationalize models
- Strong knowledge of distributed systems, performance optimization, and fault-tolerant design
- Excellent communication skills and a collaborative, team-first mindset
- Experience with MLOps tools and practices (e.g., MLflow, SageMaker, Airflow, KubeFlow)
- Familiarity with FinOps, IT financial management, or Apptio products (ApptioOne, Cloudability, Targetprocess)
- Exposure to generative AI or LLM-based solutions
- Knowledge of observability practices and tools for AI/ML-powered services