software product development jobs in seattle wa united states

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Provide technical leadership and support to UKG Pro HR engineering teams. Develop, design, and communicate a clear architectural vision and design for the teams that is aligned with the organization's goals and objectives, while keeping a product suite mindset at the forefront. Understand product requirements, drive for clarity of requirements to ensure the design is fit for purpose, and ensure design supports architecture strategy. Develops technical roadmaps and ensures that services for the suite meet established architectural guidelines and standards. Deep dive into the code to confirm design integrity and maintain a cost-effective straightforward design throughout the teams. Collaborate with cross-functional teams, including developers, operations, and product managers, to gather requirements and ensure architectural design meets the needs of internal and external stakeholders. Collaborate with peers and technical leaders to define/articulate constraints and guidelines. Define and enforce CI/CD standards, development methodologies, and quality assurance processes. Identify and mitigate risks associated with architectural decisions. Anticipate business needs 6+ months out and works with leaders to inject effort. Use resources provided by Architecture Governance on common architecture practices (standards, templates, etc.) to ensure designs and vision reflect our principles and standards. Ensure effective adoption of observability tools for proactive alerting of production performance issues, adopt service-owner mindset to ensure quick recovery from problems, and constantly seek opportunities to improve resilience of services from failures. Leverage artificial intelligence tools to identify productivity improvements for engineering teams, as also value-add features for our users. 2. Document and maintain the product & service architecture. 3. Drive strategic architecture vision and innovation. Identify and evaluate emerging technologies, industry trends, and best practices to ensure the Value Streams scalability, security, and performance. Provide architecture leadership, focusing on creating and maintaining cross-product and multi-year architecture visions. Identify architecture risks, develop mitigation strategies, and maintain architectural opportunities for all stakeholders. Understand how architecture is done across the industry; research new technology trends; identify innovations that can drive a competitive advantage for UKG products. Bachelors/Masters in engineering / Computer Science or equivalent experience 12 years of software development experience in a fast-paced environment, working through all phases of the software development life cycle. Proven experience as a lead architect or similar role, driving the architecture and implementation of complex software solutions. Possess extensive design portfolios showing high proficiency in Java based development technologies for SaaS and Multi-Tenant systems. Experience leveraging observability tools such as Datadog and Grafana for production monitoring. Experience with modern cloud technology (GCP, AWS, Azure, Kubernetes, etc.) and the ability to design a solution that operates optimally in a cloud environment, including cost optimizations, leveraging managed services, observability, etc. Strong exposure for highly reliable, scalable, secure, and decoupled solution Strong exposure of Continuous Integration and Continuous Delivery process (CI/CD) Experience in detailed analysis, feasibility studies, performance analysis and prototyping. Experience in developing Software application for Multiplatform development. Experience in object-oriented programming and design, Service oriented architecture and design patterns. Excellent leadership, communication, and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels of the organization. Excellent problems solving skills, with the ability to handle the most complex issues. Experience with relational and non-relational database technologies (SQL Server, PostGres, MySQL, MongoDB, Cassandra, etc.) Experience with modern quality practices to effectively automate testing and eliminate manual test processes will be preferred. Experience with artificial Intelligence and machine learning techniques. Experience with modern analytics technology (BigQuery, Snowflake, Tableau, Looker, etc.). Experience with messaging and event streaming solutions (Kafka, RabbitMQ, Apache Beam, Spark, etc.). 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Proven track record of leading and delivering AI/ML and Generative AI initiatives at scale in fast-paced, dynamic environments. Technical Skills: Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. Strong experience with AI, machine learning, and deep learning technologies as well as solid understanding of the software development lifecycle, object-oriented programming, concurrency, design patterns, RESTful services, and microservice architecture. AI Tools and Cloud Technologies: Experience with cloud platforms (AWS, Google Cloud, Azure), with a focus on AI/ML deployment (e.g., VertexAI, GKE, BigQuery, Kubeflow, TensorFlow Serving). Familiarity with MLOps practices and tools for model deployment and monitoring (e.g., Terraform, GitHub Actions, Concourse). Leadership and Collaboration: Strong people management and leadership skills, with experience leading cross-functional teams. Proven ability to mentor engineers, manage competing priorities, and align team efforts with business objectives. Agile Experience: Strong understanding of agile methodologies, with experience leading teams in an agile environment. Knowledge of best practices for managing sprints, tasks, and project timelines. Ability to communicate complex technical concepts to non-technical stakeholders and build strong working relationships across the organization. Experience working with large language models (LLMs) or fine-tuning open-source models like GPT. Familiarity with modern AI development tools, such as Jupyter notebooks, Kubernetes, Docker, and CI/CD pipelines. Experience in high-compliance or enterprise-grade environments with a focus on AI ethics, privacy, and security. Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field. 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Advanced AI Product Development: o Lead the development of state-of-the-art generative AI solutions, leveraging advanced techniques such as transformer models, diffusion models, and multi-modal architectures. o Drive innovation by exploring and integrating emerging AI technologies and best practices. Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field; Ph.D. is preferred but not required. Experience: 10+ years of professional software development experience, including 5+ years in AI/ML or GenAI. Proven track record of designing and deploying scalable, production-grade AI solutions. o Deep expertise in Python and frameworks such as TensorFlow, PyTorch, FastAPI, and LangChain. o Advanced knowledge of AI/ML algorithms, generative models, and LLMs. o Proficiency with cloud platforms (e.g., GCP, AWS, Azure) and modern DevOps practices. o Strong understanding of distributed systems, microservices architecture, and database systems (SQL/NoSQL). Leadership Skills: Demonstrated ability to lead complex technical initiatives, influence cross-functional teams, and mentor engineers at all levels. Problem-Solving Skills: Exceptional analytical and problem-solving skills, with a proven ability to navigate ambiguity and deliver impactful solutions. Collaboration: Excellent communication and interpersonal skills, with the ability to engage and inspire both technical and non-technical stakeholders. AI/ML Expertise: Experience with multi-modal models, reinforcement learning, and responsible AI principles. Cloud & Infrastructure: Advanced knowledge of GCP technologies such as VertexAI, BigQuery, GKE, and DataFlow. Thought Leadership: Contributions to the AI/ML community through publications, open-source projects, or speaking engagements. 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Develop and communicate a cohesive architectural vision that aligns with business goals, enabling the seamless integration of GenAI capabilities across our product suite. Technical Leadership: Serve as the primary technical visionary for generative AI, providing hands-on guidance in advanced methods (e.g., transformer models, diffusion models, GANs) and setting technical standards that ensure scalability, security, and efficiency. Cross-Functional Collaboration: Work closely with executive leadership, product management, data science, and engineering teams to establish and prioritize GenAI initiatives. Collaborate with cross-functional teams to ensure alignment on requirements and objectives, driving the infusion of AI capabilities across products. Innovation & Research: Conduct hands-on, advanced research in generative AI, staying current with emerging technologies, industry trends, and best practices. Lead the exploration and implementation of state-of-the-art GenAI techniques to enhance product value and drive a competitive edge. Mentorship & Culture Building: Mentor and influence senior engineering leaders, fostering a culture of AI excellence, thought leadership, and continuous innovation. Champion best practices in AI/ML development, CI/CD processes, and quality assurance to ensure high standards across the organization. Community Engagement: Act as an ambassador for generative AI internally and externally, representing UKG in the AI community through publications, speaking engagements, and industry forums. Scalable Solutions: Oversee the deployment of large-scale AI models, ensuring they are optimized for performance, cost, and resource efficiency in production environments. Establish guidelines for high-quality, production-ready AI/ML systems that can scale with business needs. 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AI Methodologies: In-depth knowledge of generative AI methodologies, including transformer models, diffusion models, GANs, large language models, and multi-modal architectures. Familiarity with NLP and machine learning algorithms, such as linear and logistic regression, decision trees, and clustering methods. Industry Influence: Recognized thought leader in AI, with a record of publications in top-tier AI conferences/journals (e.g., NeurIPS, ICML, CVPR) and a strong network within the AI research community. Problem-Solving & Strategy: Exceptional problem-solving skills and a proven ability to influence and implement long-term AI-driven strategic initiatives. Compliance & Responsible AI: Experience working in high-compliance environments or with privacy-preserving AI techniques. Strong familiarity with trends in responsible AI, model interpretability, and ethical AI practices. Optimization Expertise: Proven record of optimizing AI models for cost-efficiency at scale through model compression, distillation, and efficient deployment strategies. 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