
Senior Software Engineer
Our client is standing up a new AI Solutions capability and they are looking for a
Senior Backend/Platform Engineer
to design and build a reusable GenAI content-generation platform. This platform will power multiple internal AI products that share a common pattern: enterprise data + LLM orchestration → generated documents/emails/reports. The goal is to build the core platform once, so downstream teams can ship new GenAI experiences quickly and safely—without re-inventing the stack every time.
What you’ll do:
· Own backend architecture for a shared GenAI content-generation platform used by multiple internal products.
· Design multi-tenant patterns (config isolation, data segmentation, policy enforcement) and clean service interfaces.
· Implement LLM orchestration pipelines for high-quality document/report generation (templating, context selection, post-processing).
· Build or integrate retrieval components (semantic search/RAG, vector stores) suitable for regulated environments.
· Partner with stakeholders to ensure security-by-design, auditability, and operational excellence.
What we’re looking for:
· 8+ years of software engineering experience; Python is your primary language.
· Built and shipped a multi-tenant platform in production (GenAI platform experience strongly preferred).
· Strong AWS experience (architecture + implementation).
· Hands-on experience with at least one: RAG/semantic search, document-generation pipelines, multi-agent systems.
· Experience delivering LLM-enabled systems in regulated or highly controlled enterprise environments.
Nice to have:
· Experience with private model hosting / in-VPC model endpoints.
· Familiarity with Bedrock/SageMaker or comparable model hosting patterns.
· Experience building internal developer platforms (SDKs, templates, CI/CD scaffolding).
How success will be measured (high level):
· A clear, pragmatic architecture and “golden path” for downstream teams (design doc + reference implementation).
· A production-ready, multi-tenant platform MVP that supports at least one end-to-end use case.
· Reusable building blocks for retrieval (RAG/semantic search), orchestration, guardrails, and output post-processing.
· Operational readiness: logging/metrics/tracing, dashboards, alerting, deployment pipeline, and runbooks.
Start: ASAP (flexible).
Location: Remote-friendly within the U.S. (or aligned time zones) • Occasional on-site may be requested depending on team needs.
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