Dolby
From Dolby's careers page
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As a member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones.
Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you’ll see and hear the results of your work everywhere, from movie theaters to smartphones. We continue to revolutionize how people create, deliver, and enjoy entertainment worldwide. To do that, we need the absolute best talent. We’re big enough to give you all the resources you need, and small enough so you can make a real difference and earn recognition for your work. We offer a collegial culture, challenging projects, and excellent compensation and benefits, not to mention a Flex Work approach that is truly flexible to support where, when, and how you do your best work.
We're building Dolby's Centralized Agentic AI Framework — a shared platform that brings safe, governed, cost-aware AI agents into every team's GitLab workflow.
You'll be a hands-on engineer building and extending this platform — writing the Lambdas that orchestrate agents, integrating Bedrock with GitLab CI, hardening the security and observability layers, and shipping new agent capabilities that any team can adopt without re-architecting.
Build agent orchestration — implement Router Lambdas, SQS-based queueing, and Bedrock Agent invocation
Integrate with GitLab CI/CD — design .gitlab-ci.yml patterns where agent invocations run as pipeline stages, consume branch/diff/test context, emit artefacts, and gate downstream stages on agent pass/fail signals.
Develop shared Action Groups — build the AWS Lambda-backed tools
Design Knowledge Bases — iUtilise AWS Bedrock Knowledge Base / OpenSearch / S3 so agents reason over shared organizational context, not isolated prompts.
Implement Bedrock Guardrails — input/output filters, sensitive-data scrubbing, content/word filters, and per-agent permission boundaries enforced by design.
Implement TokenOps controls — model tiering and routing via an LLM gateway, semantic caching, context-window management
Instrument everything in AWS — CloudWatch dashboards, audit trails, trace logging of every agent invocation (input, output, decision, tokens, cost) for compliance and debugging.
Required (3–5 years professional experience)
Strong Python, AWS SDK Python for building production Lambda functions and event-driven services.
Solid AWS experience: Lambda, API Gateway, SQS, EventBridge, IAM, Secrets Manager, CloudWatch.
Amazon Bedrock specifically: Agents, Action Groups, Knowledge Bases, Guardrails.
Hands-on experience integrating with LLM APIs — Bedrock, OpenAI, Anthropic, or similar.
Familiarity with CI/CD platforms — GitLab CI strongly
A security mindset: least-privilege IAM, secrets handling, input validation, awareness of prompt injection and data-leak risks in LLM workflows.
Comfortable with observability — structured logging, metrics, tracing — and writing code that's debuggable in production.
Nice to have
Experience building developer platforms or internal tooling — you've shipped something other engineers depend on daily.
Familiarity with agent frameworks (Bedrock AgentCore) and their tradeoffs.
How you work
You write small, focused services with clear contracts — not monoliths.
You treat extensibility as a feature: new triggers/agents/tools shouldn't require touching unrelated layers.
You think about the developer experience of the teams who'll use your platform, not just whether the code runs.
You're comfortable with ambiguity — agentic systems are non-deterministic, and you debug them empirically.
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