AWS Jobs in Web3

WHO WE ARE: Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders.WHO YOU ARE:  Generative AI Engineer will be responsible to design, build, and operate production LLM systems—RAG services, eval/guardrail pipelines, and API integrations—used across the enterprise. WHAT YOU'LL DO:  

Own backend services for GenAI features (Python/FastAPI or TypeScript/Node), from design to production. Build RAG pipelines end-to-end: chunking, embeddings, vector indexes, retrieval, reranking, grounding, and response synthesis. Build/extend MCP integrations for major internal applications and APIs. Implement LLM evaluation & guardrails: prompt/unit evals, Ragas, Langfuse, LangSmith, A/B tests, hallucination & safety checks, feedback loops. Stand up LLMOps/MLOps: CI/CD for models & prompts, dataset/version management, feature stores, tracing, monitoring, and cost controls. Create SDKs/REST/GraphQL integrations with internal systems; handle auth (OAuth/JWT), rate limits, retries, and backoff. Drive observability (metrics, tracing, logs), SLOs, and incident response; partner with SRE for reliability. Collaborate with product and security on requirements, data governance, and privacy-by-design. Mentor peers; raise code quality through reviews, design docs, and reusable components.

WHAT YOU’LL NEED:

Total 5-9 years of experience is required. Backend strength: Python (FastAPI, Pydantic, async) or TypeScript/Node (Express/Fastify/Next API routes); testing (pytest/jest), Git/PR hygiene, CI/CD. GenAI hands-on: LLM prompting/tool use, context management, streaming, and at least one RAG system taken to production (or a rigorous POC with metrics). Vector search: FAISS/pgvector/Pinecone/Weaviate/Milvus/Qdrant; embeddings pipelines; caching & cold-start strategies. Ops for AI: Practical MLOps/LLMOps/AIOps—model/prompt versioning, data contracts, evaluation harnesses, cost/perf monitoring, rollbacks. Cloud & infra: Docker, Kubernetes (or serverless), one major cloud (AWS/Azure/GCP), secrets management, IaC basics. Security & governance: PII handling, RBAC, audit trails, and least-privilege design.

 Nice to have

LangChain/LlamaIndex/LangGraph, Agentic AI, OpenAI/Azure, Gemini, OpenAI/Bedrock/Vertex SDKs; MCP (Model Context Protocol) tools/adapters. Retrieval enhancements: hybrid search, re-rankers, prompt caching, toolformer/function calling. Data systems: PostgreSQL, Redis, Kafka/SQS; batch & streaming pipelines. Observability: OpenTelemetry, Prometheus, Grafana; latency/cost optimization. Basic frontend for internal tools (React/Next.js) to wire quick admin consoles. 

WHAT’S IN IT FOR YOU?  At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

LI-SN1