Staff Engineer

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
As a Staff AI Engineer - Researcher you will lead the research and development of next-generation Generative AI capabilities, agentic architectures, and model infrastructure at scale. You will architect systems that extend beyond foundational models — enabling autonomous reasoning, retrieval-augmented generation, multi-modal workflows, and real-time deployment.

As an Applied AI researcher you'll work across the full AI stack — from fine-tuning LLMs to orchestrating self-healing multi agents orchestration and real-time custom RAG stacks, integrating seamlessly into core products and engineering platforms. As You'll lead innovative research and rapid prototyping in Generative AI, developing quick POCs that demonstrate tangible solutions to complex business challenges for both technical and business stakeholders.

What You'll Do
Architect Next-Gen AI Systems
Design and implement LLM-native systems including autonomous agents, multi-agent collaboration, planning, and tool use

• Develop custom fine-tuned models optimized for latency, scale, and safety
• Build streaming and asynchronous inference systems for responsive applications

Lead Infrastructure for Model Lifecycle

• Own pipelines for training, fine-tuning (SFT, DPO, LoRA), and deployment
• Manage RAG indexing and content refresh pipelines
• Implement experiment tracking, artifact lineage, and reproducibility tooling
• Develop tools for continuous evaluation and large-scale performance monitoring

Advance RAG and LLM Tooling

• Build low-latency RAG pipelines using frameworks like LlamaIndex, LangGraph, CrewAI, AutoGen.
• Design scalable vector store architectures (Weaviate, Qdrant, FAISS)
• Implement agent stacks with memory, planning, and semantic self-refinement

Productionize Multi-Modal and Multi-Agent Systems

• Deploy and optimize foundation models (text, image, code, speech) across distributed GPU infrastructure.
• Architect agent execution environments supporting parallelism and context passing.
• Integrate inference workloads using Ray Serve, vLLM, Triton, or similar tools

Must-Have
WHAT YOU'LL NEED:
Qualifications

• Bachelor's or Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or related field. PhD candidates are preferred.
• 3–7+ years of professional experience in AI/ML development, ideally with deep systems-level engineering skill and ownership.
• Proven experience at an AI-first company or contributions to AI/ML research or open-source projects are highly desirable.

Bonus

• Publications in top-tier AI/ML conferences (NeurIPS, ICML, ACL, ICLR)
• Familiarity with multi-modal model alignment and self-improving agents
• Open-source contributions to ML tooling, libraries, or agent frameworks
• Experience with model compression, distillation, quantization workflows

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 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