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 This role will take a workstream and drive it to production: agent services, the shared agentic platform, building out additional tools for agent swarms to use and integrating with existing applications. Today the work centers on agent runtimes, a company-wide code-review agent, MCP servers, agent swarms, and a spec-driven delivery frameworks. As the team moves into new agentic tools and areas, this role helps lead the adoption. You'll be a part of the Entertainment Platform Architecture team that builds and runs the agentic AI systems for Viasat's Entertainment org supporting Commercial Aviation Live TV, In-flight Entertainment, and Content Delivery Platform capabilities. We are seeking an Agentic Engineer to build alongside the Architect for the org and own workstreams end to end. This is a hands-on engineering role. You build, review, and operate fully agentic systems. You also mentor engineers and help set how the org adopts agentic AI setting the foundation and creating prototypes or platforms that can be expanded by other team . The role reports to the Lead Platform Architect in the Entertainment organization. The day-to-day Agentic Engineering Build and ship agentic AI applications end to end with the architect and product team , from the data layer through the agent runtime to the production interface. Extend and operate production agent services, including the company-wide code-review agent. Own the evaluation harnesses, observability, and guardrails that measure quality, cost, and safety. Build MCP servers and integrations that give agents one governed interface to internal systems and data. Build and maintain reusable agent templates, libraries, and components, so a new agent starts from a governed, deploy-anywhere baseline that other teams adopt. Build and operate agent swarms and automations that take over recurring operational work for both process and development flows. Advance the spec-driven delivery framework (spec, implement, test to green CI, pull request) that runs many parallel feature cycles a day. Deploy on a build-to-image architecture across GCP and AWS. Use Terraform and infrastructure-as-code, and route services through the governed gateways. Build to the org's AI architecture standards and responsible-AI guardrails. Emerging Agentic Work Prototype, evaluate, and productionize new agentic frameworks and developer-productivity tools as the team moves into new areas. Run structured experiments and proofs-of-concept with documented evaluation criteria and clear OKRs. Mentoring and Enablement Run daily code review and mentor engineers on agentic development, prompt engineering, and internal AI tooling. Contribute to the monthly AI forum: live build-an-agent tutorials, architecture and ADR reviews, and readouts. Write and maintain internal documentation, patterns, and getting-started guides for the team's agentic tooling. Additional Details This position is site-based. Site‑based employees work 3+ days (60%+) per week from a Viasat office or work location within a standard five‑day work week. Viasat embraces a flexible work environment and onsite/hybrid work is determined by individual roles and teams. Relocation assistance is available pending eligibility. What you'll need Experience Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 5+ years of professional software engineering experience, with a track record of shipping and operating production systems. Hands-on experience with modern AI/LLM technologies: agentic workflows, tool and function calling, retrieval-augmented generation, evaluation, and observability. Experience owning a workstream or service end to end, from design through production operation. Technical Skills (Required) Strong Python and TypeScript/React. Comfortable building full-stack, from the data layer to the production UI. Hands-on agentic

AI:

agent runtimes and orchestration, Agent Development Kit (ADK) or Claude SDK, and Model Context Protocol (MCP) servers. Prompt engineering alone is not enough. GCP (Vertex AI, Cloud Run, BigQuery, and related services) and infrastructure-as-code with Terraform, Terragrunt, or OpenTofu.

Modern application architecture:

APIs, containers, CI/CD, and multi-repo delivery.

Comfort with data:

SQL, data pipelines, and how data quality affects AI outcomes. Leadership and Collaboration Self-directed. Takes a delegated workstream and drives it to production with little oversight. Not afraid to break things, and fix them. Strong written and verbal communication. Can explain agentic systems to non-technical partners. Track record of mentoring engineers through code review. Works well as one half of a close two-person building partnership: fast feedback, shared ownership, high trust. What will help you on the job Experience building or operating an inner-source or platform-engineering program adopted by teams outside the originator's reporting line. Experience with AWS and on-prem or self-hosted model serving in addition to GCP. Experience with evaluation harnesses, agent observability, and cost and safety guardrails at production scale. Familiarity with developer-productivity AI tools such as Claude Code, Cowork, Gemini, or Copilot. Background in web platforms, portals, or customer-facing product engineering. Exposure to satellite communications, telecommunications, aviation, or other regulated industries. Experience running training, brown bags, or technical talks. Salary range $140,500.00 - $221,500.00 / annually. For specific work locations within San Jose, the San Francisco Bay area and New York City metropolitan area, the base pay range for this role is $174,000.00- $261,000.00/ annually At Viasat, we consider many factors when it comes to compensation, including the scope of the position as well as your background and experience. Base pay may vary depending on job-related knowledge, skills, and experience. Additional cash or stock incentives may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered. Learn more about Viasat's comprehensive benefit offerings that are focused on your holistic health and wellness at https://careers.viasat.com/benefits. 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 .

Qualifications:

Experience Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 5+ years of professional software engineering experience, with a track record of shipping and operating production systems. Hands-on experience with modern AI/LLM technologies: agentic workflows, tool and function calling, retrieval-augmented generation, evaluation, and observability. Experience owning a workstream or service end to end, from design through production operation. Technical Skills (Required) Strong Python and TypeScript/React. Comfortable building full-stack, from the data layer to the production UI. Hands-on agentic

AI:

agent runtimes and orchestration, Agent Development Kit (ADK) or Claude SDK, and Model Context Protocol (MCP) servers. Prompt engineering alone is not enough. GCP (Vertex AI, Cloud Run, BigQuery, and related services) and infrastructure-as-code with Terraform, Terragrunt, or OpenTofu.

Modern application architecture:

APIs, containers, CI/CD, and multi-repo delivery.

Comfort with data:

SQL, data pipelines, and how data quality affects AI outcomes. Leadership and Collaboration Self-directed. Takes a delegated workstream and drives it to production with little oversight. Not afraid to break things, and fix them. Strong written and verbal communication. Can explain agentic systems to non-technical partners. Track record of mentoring engineers through code review. Works well as one half of a close two-person building partnership: fast feedback, shared ownership, high trust.