Mid-level Data
1 week ago
* 3+ years in backend/data/ML engineering with recent hands‑on work in LLM/agentic or retrieval systems.
* Strong Python; TypeScript/Node experience is a plus. Solid engineering hygiene: tests, CI/CD, containers, infrastructure as code and observability.
* Experience with an agent framework or graph runtime (e.g., state machines/graphs, function calling, tool use) and reliability controls.
* RAG experience using AWS‑centric options (e.g., Amazon OpenSearch Serverless vector search or Aurora PostgreSQL with pgvector) and citation practices.
* Understanding of data governance (RBAC/ABAC, audit trails, privacy by design, data residency) and willingness to adopt ISO‑aligned AI governance.
* Familiarity with evaluation frameworks and online experiments; comfortable instrumenting metrics for cost, reliability and quality.
* Team‑first mindset aligned to our values: customer‑focused, collaborative, integrity‑led and outcomes‑obsessed.
Nice to have
* Exposure to agent registries/marketplaces or AMPs; MCP or similar agent protocols.
* Policy engines and guardrails (e.g., AWS Verified Permissions/OPA‑style), feature flags, rate‑limiting and quotas.
* Eventing/queues and integration patterns (e.g., Amazon EventBridge, SQS/SNS; experience with iPaaS/SaaS connectors).
* Experience defining domain ontologies/taxonomies and data contracts.
* Cost/performance tactics for LLMs (routing, caching, summarisation, batch inference) and experience with Amazon Bedrock, Knowledge Bases and Guardrails for Bedrock.
Job Type: Contract
Benefits:
- Health insurance
Work Location: Remote
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