Software Engineer Agentic AI Platform
Indexed description
About The Role
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.
What You'll Do
- 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.
- 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.
- Experience with SAST/DAST/SCA tools
- 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.
- 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.
Dolby Poland Sp. z o.o.
Business Garden, Building G
ul. Legnicka 48
Wrocław, 54-202, Poland
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