Agentic Engineer, Entertainment

About the role

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.

Responsibilities

• 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.
• 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 teams.

Requirements

• 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.
• 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.
• Comfort with data: SQL, data pipelines, and how data quality affects AI outcomes.

Skills

• Strong Python and TypeScript/React.
• Hands-on agentic AI: agent runtimes and orchestration, Agent Development Kit (ADK) or Claude SDK, and Model Context Protocol (MCP) servers.
• Comfort with data: SQL, data pipelines, and how data quality affects AI outcomes.
• Experience with 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.

Qualifications

• 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.
• 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.
• Comfort with data: SQL, data pipelines, and how data quality affects AI outcomes.

Benefits

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.

Pay

$140,500.00 - $221,500.00 / annually.

Schedule

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.