Viasat, Inc.
Senior Solutions Architect - Growth Analytics
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About us
One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team.
What you'll do
Our team builds data-driven products that directly drive Viasat's revenue growth by transforming how our commercial and customer-facing teams operate. We create innovative data and software tools that sales, account management, and customer success teams use to close more deals, retain customers, and deliver better customer experiences.
As Senior Solutions Architect, you'll co-lead the technical architecture and development of our entire platform ecosystem: web portals, automated document generation systems, and cloud applications that process billions of records. You'll collaborate on end-to-end technical decisions, from selecting frameworks to designing integrations between BigQuery data pipelines, Salesforce, and enterprise authentication systems. Working in Python, AWS Lambda, Next.js/React, and Terraform, you'll architect high-performance solutions while mentoring team members and contributing innovative ideas for future capabilities.
Your technical decisions directly influence how hundreds of commercial and customer-facing professionals across global business units identify prospects, prioritize opportunities, retain accounts, and deliver differentiated customer experiences. A key part of the role is evaluating and integrating emerging AI capabilities — including LLM-powered features, AI agent frameworks, and MCP servers — to accelerate both internal tooling and customer touchpoints.
You'll join an existing Senior Solutions Architect and share technical ownership of the platform, dividing focus across features and initiatives. You'll work with Analytics Engineers in your team who build the data pipelines powering your applications, sales teams across business units who provide direct feedback, product and commercial teams who understand customer needs as well as data engineers and IT teams who help scale solutions. This cross-functional exposure gives you unique perspective on both technology and business context. You'll help scale successful, well-loved tools from MVP stage to enterprise-grade platforms serving new markets, working in a small, collaborative team with startup pace but enterprise resources and mandate.
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The day-to-day
You'll architect new applications and features across the full stack, from designing API endpoints and service architectures to implementing frontend interfaces. Daily work involves reviewing technical designs with Analytics Engineers, making architectural decisions on system integrations, and writing code in Python and TypeScript to implement solutions from infrastructure through user interface.
A typical day includes conducting proof-of-concepts for new tools and technologies, evaluating their fit for the platform architecture, and presenting technical recommendations to the team. This increasingly includes AI-powered capabilities: evaluating LLM APIs (such as Anthropic Claude or OpenAI), building MCP servers to expose internal data to AI agents, and prototyping agentic workflows that automate repetitive commercial processes. You'll investigate and resolve production bugs, optimize web portal performance and rendering efficiency, debug Lambda functions, and refactor components to improve reliability and maintainability. You'll design efficient data movement patterns in the cloud to handle high-volume datasets and ensure applications remain responsive under load.
You'll collaborate with the Product Lead to define technical requirements for new features, propose implementation approaches, and estimate development effort. This includes designing integration patterns between systems, implementing authentication and authorization systems for enterprise portals, specifying API contracts, and selecting scalable technologies that can grow with the platform. You'll also spend time on infrastructure work: deploying services via Terraform, configuring CI/CD pipelines, architecting document generation systems, and ensuring applications meet performance and security requirements for enterprise deployment.
What you'll need
- Expert-level Python development experience building production applications
- Expert-level AWS experience, including Lambda, ECS/Fargate, S3, and API Gateway
- Proven experience deploying and managing containerized applications using Docker
- Strong SQL skills and experience working with data warehouses
- Hands-on experience with Infrastructure as Code tools, particularly Terraform
- Proficiency with Git and modern CI/CD workflows
- Demonstrated ability to design and implement multi-component software systems from architecture through production deployment
- Experience making technical architecture decisions and trade-offs in fast-paced environments
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What will help you on the job
- Experience with modern web development frameworks, particularly Next.js, React, and TypeScript
- Familiarity with Google Cloud Platform services, especially BigQuery and Cloud Run
- Knowledge of enterprise authentication patterns including SSO, SAML, OAuth, and RBAC
- Experience processing and optimizing applications that work with high-volume datasets at scale
- Background in B2B SaaS, sales enablement tools, or CRM platforms
- Track record of scaling MVPs into enterprise-grade platforms
- Experience working in Agile environments using tools like JIRA
- Comfort working across the full stack from infrastructure to frontend
- Ability to mentor junior engineers and establish technical best practices
- Understanding of how technical decisions impact business outcomes and user adoption
- Experience with automated document generation or data visualization libraries
- Experience working with LLM APIs (e.g. Anthropic Claude, OpenAI) and building AI-powered features in production applications
- Familiarity with the Model Context Protocol (MCP) or AI agent frameworks for tool-augmented LLM workflows
- Understanding of customer lifecycle touchpoints beyond sales — e.g. onboarding, customer success portals, and self-service tooling
EEO Statement
Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic. If you would like to request an accommodation on the basis of disability for completing this on-line application, please click here.
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