The Principal Software Architect - GenAI acts as an architecture leader in a domain area in multiple activities and teams.
Responsible for the high-level design/architecture decisions and drives continuous improvement in architecture and engineering across set of software products/services.
Additionally responsible for solutioning and planning for the incorporation of generative AI capabilities across the entire Duck Creek Suite.
Acts as a Domain Architect for the GenAI domain, leading and representing the design/architecture decisions of that domain area.
Provides architectural and technical leadership, participating and leading with Engineering Communities of Practice.
Refines technical backlog items and creation of the overall solution concept and architectural direction for multiple engineering teams.
Provides guidance and support to the developers in multiple engineering teams across our product suite in the completion of stories against design/architecture plans.
Mentor and help develop engineers and architects in their career growth.
Drives and coordinates our technical position with key technology vendors.
Can be hands-on, designing and coding solutions for Agile stories with key architectural impact.
Requirements
Bachelor’s or Masters Degree and/or equivalent experience relevant to functional area
7+ years of engineering and/or architecture experience
5+ years supervisory and strategic leadership experience
Generative AI Expertise
Experienced in creating solutions incorporating Generative AI platforms and tooling into production products.
Hands-on experience with LLM integration, RAG pipelines, vector databases, prompt engineering, and hallucination mitigation strategies.
Familiarity with fine-tuning and model evaluation techniques for large language models.
Strong command of object-oriented programming principles with expert knowledge of Java or C#, and Python.
Proficiency with relevant frameworks and libraries such as Spring Boot, .NET Core, TensorFlow, PyTorch , LangChain , Hugging Face Transformers, and OpenAI/Anthropic SDKs.
Experience in model lifecycle management, including training, deployment, monitoring, and retraining.
Skilled in MLOps practices: CI/CD for ML, model versioning, drift detection, and governance.
Knowledge of cost optimization strategies for LLMs in production environments.
Expert in distributed software patterns (DDD, microservices, serverless, event-driven) and cloud-native architectures (AWS, Azure, GCP).
Experience building monitoring, alerting, and observability for maintaining high SLAs in SaaS products.
Proficient in applying data security, compliance, and responsible AI principles across the solution lifecycle.
Promote inner-sourced tooling and shared technology standards across teams.
Leverage AI tools and practices to enhance engineering productivity, decision-making, and innovation.
Benefits
Flexible work environment
Medical, dental, vision, life and disability insurance
401(k) Retirement Plan
Flexible Spending & Health Savings Account
Paid holidays, vacation, and volunteer time
Employee assistance program and other benefits
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