Key Responsibilities
- Build and ship LLM apps & agents: Deliver internal copilots and customer/agent-facing automations with clear SLAs, rollbacks, and observability from day one.
- Own RAG pipelines: Design ingestion, chunking, embeddings, indexing, hybrid search/rerank, and retrieval evaluation; track retriever quality via offline golden sets and online metrics.
- AWS Infrastructure & Orchestration: Design and implement scalable AWS architectures, including AWS AI features such as Bedrock, IAM, knowledge bases, secure secrets and policy enforcement, automated provisioning, and resource-usage governance as core platform capabilities.
- Observability & SRE for AI: Add tracing, prompt/agent version lineage, eval dashboards, and regression alerts; establish golden datasets and canary tests.
- Guardrails & governance: Enforce PII redaction, safety filters, role-based access, audit logs, and human‑in‑the‑loop review paths to control quality and risk.
- CI/CD for AI artifacts: Version and deploy prompts, tools, agents, and retrieval pipelines; support blue/green and shadow deploys with automatic rollback triggers.
- Cost & performance: Cut run‑rate spend through caching, truncation, batching, autoscaling, and model routing; establish clear unit economics per workflow.
- Developer enablement: Provide templates, SDKs, and high‑quality abstractions that let product teams ship safely without bespoke plumbing; improve developer experience.
- Platform integration: Build primarily in Python and Metaflow (Outerbounds); deploy on AWS (Bedrock + core services) and OpenAI; use Cursor in daily workflows; help evaluate and, when appropriate, run on Databricks.
- Production posture: Participate in on‑call, author runbooks, and remove single‑thread risk for AI services; drive reliability and resilience akin to ML Ops.
What You’ll Need to Succeed:
- Experience: 5–10 years of professional software engineering (or equivalent) with 2+ years building AI/LLM applications; portfolio of shipped AI projects (links to code, demos, or case studies).
- Exploration: Demonstrated passion for relentless exploration of the latest AI models, frameworks, and tooling, ensuring constant adoption of state-of-the-art innovations in the workflow.
- LLM product engineering: Hands‑on with some/all of OpenAI, Bedrock, Huggingface/Ollama/vLLM; MCP servers and function/tool calling, multi‑turn orchestration, streaming, and prompt/version management.
- RAG expertise: Practical experience designing and tuning retrieval systems (chunking, embeddings, hybrid search, reranking), integration with vector database, and measuring retrieval quality.
- Full‑stack or equivalent backend depth: Comfortable building APIs/services and simple UIs where needed; strong fundamentals in Python and modern packaging/testing.
- DevOps & deployment: CI/CD, containers, cloud fundamentals (AWS), and runtime performance tuning; experience operating services in production.
- Platform & orchestration: Metaflow (Outerbounds) preferred; Databricks familiarity is a plus; ability to integrate data/feature pipelines and schedule/operate flows.
- Observability & testing for AI: Tracing and logging, expertise in tools like Datadog, Dynatrace or Grafana where relevant for AI monitoring is essential.
- Cost, quality, and risk mindset: Comfortable optimizing latency/throughput/cost, and implementing guardrails for PII/safety/compliance.
- Collaboration & mentorship: Partner effectively with data scientists, analysts, and engineers; promote best practices and high‑leverage abstractions.
- Bonus points: Fine‑tuning or distillation experience; Kubernetes or FastAPI exposure; familiarity with Snowflake or similar warehousing for retrieval sources.
Top Skills
What We Do
Best Egg is a consumer financial technology platform that aims to help people feel more confident about their everyday finances through a suite of products and resources. Our digital financial platform offers simple, accessible, and personalized financial solutions including personal loans, credit cards, and a financial health resource center.
Our culture and values are one of the core reasons why our customers keep returning to Best Egg. We are committed to championing a culture of inclusiveness and diversity of thought, and we focus on providing a safe, flexible, and collaborative work environment. Our associates are encouraged to engage in creative problem solving, and we promote opportunities for growth and enrichment across the organization.
If you are inspired by inspiring others, Best Egg is the place for you.







