Senior AI Software Engineer

*We offer a flexible working policy that supports a healthy balance between personal and professional well-being. This role requires in-office presence on Tuesdays & Thursdays to collaborate, connect, and learn from peers - while also maintaining the flexibility for meaningful work-life balance.* **Being a Senior AI Software Engineer at iManage Means…** You are passionate about building and deploying AI systems that work at scale in production. You will work within the Applied AI team alongside engineers, data scientists, and product stakeholders to develop the AI capabilities that power iManage’s enterprise work platform, including Ask iManage, our generative AI document assistant, as well as document classification, extraction, and LLM-driven features that directly impact how knowledge workers search, organize, and understand their most critical information. You bring hands-on depth in both model development and the infrastructure required to ship it reliably, and you thrive at the intersection of machine learning, software engineering, and cloud infrastructure. **iM Responsible For…** - Owning the end-to-end ML lifecycle for AI systems from model development and evaluation through to scalable production serving, generative AI document intelligence, and agentic system use cases - Deploying and optimizing ML/AI systems on GPUs and Kubernetes-based cloud infrastructure, including AKS or equivalent platforms, while balancing trade-offs across scalability, latency, performance, operational complexity, and cost efficiency - Designing and implementing production-ready LLM applications and APIs with monitoring, observability, and integration testing built in - Applying modern engineering practices for production AI systems, including containerized services, CI/CD pipelines, model and version tracking, and release governance - Collaborating with product and business stakeholders to translate requirements into viable technical solutions - Conducting code reviews and providing constructive feedback to team members - Contributing to best practices and standards for AI engineering across the team **iM Qualified Because I Have…** - A Bachelor’s, Master’s, or Ph.D. in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Statistics, or a related field - 3+ years of experience in ML/AI engineering or software engineering - Hands-on experience building and shipping LLM systems into production - Deep proficiency in Python and modern AI frameworks, including PyTorch and Hugging Face - Solid understanding of ML fundamentals including hands-on experience with both traditional ML and modern generative AI and transformer architectures - Demonstrated experience fine-tuning language models and deploying them to production - Experience with GPU optimization for training and inference workloads - Experience with Kubernetes deployment on cloud infrastructure (Azure, AWS, or GCP) to optimize systems for scalability, latency, performance, and cost efficiency - The ability to work collaboratively across teams, communicate with precision, and take ownership from prototype to production **Bonus Points If I Have…** - Experience with distributed training frameworks (e.g., PyTorch Distributed, Ray) and inference optimization tools (e.g., vLLM, SGLang) - Experience with agentic engineering, including agent harness and agent memory, and orchestration frameworks such as LangChain, LlamaIndex, or similar tools - Experience with knowledge graphs and multimodal LLMs - Familiarity with AI/ML observability tools and model lifecycle management best practices *Don't meet every qualification listed above? Studies show that women and people of color are less likely to apply to jobs unless they meet all qualifications. At iManage, we are committed to building a diverse and inclusive environment, and encourage everyone to show up as their full authentic selves. We welcome those that come with a growth mindset and a hunger for learning; so, if you are…