AI Engineer, Agent Platform
About The Position
NewsBreak is seeking an AI Engineer to join their Agent Platform team. This role will focus on building the core infrastructure that powers NewsBreak's next-generation AI products, including local-news synthesis agents and paid-growth agents. The engineer will be responsible for the end-to-end ownership of this platform layer, working within a small, agile team that emphasizes weekly shipping, close collaboration with product teams, and a strong focus on evaluation and observability. The existing codebase already supports multiple agents in production, and this role will be instrumental in developing future capabilities.
Requirements
- Demonstrable experience shipping an AI product with real users (e.g., a side project, internal tool, open-source agent, or startup MVP).
- Active, hands-on familiarity with modern AI development tooling (e.g., Cursor, Claude Code, Codex, v0, or equivalents).
- Ability to work end-to-end independently: backend, frontend, deployment, instrumentation, and iteration.
- Developed perspective on AI agent design: context management, tool-calling protocols, eval strategy, and the tradeoffs between fine-tuning, prompting, and scaffolding.
- Strong proficiency in Python (or Go / Node) with solid backend engineering experience (APIs, databases, queues, caches) and an understanding of how system design needs evolve with scale.
- Sufficient frontend capability (React or Next.js) to ship functional internal tools independently.
- Product sensibility: willingness to push back when something feels off, and a habit of thinking about the end user alongside the technical architecture.
Nice To Haves
- Experience building or operating a multi-agent system in production (orchestration, sub-agents, MCP, skills).
- Hands-on experience with eval frameworks (LM-eval, custom harnesses, LLM-as-judge), prompt iteration workflows, or fine-tuning (LoRA / RLHF / DPO).
- A public artifact — GitHub repo, technical blog, paper, or demo — that reflects how you approach problems.
- Experience integrating LLMs with complex, real-world data (news, ads, geo, user behavior) at scale.
Responsibilities
- Build the agent runtime that orchestrates context assembly, tool invocation, model routing, and workflow tracking across multiple agentic products.
- Design the eval and observability harness that runs thousands of agent traces per day, surfaces regressions before they ship, and turns production failures into actionable improvements.
- Own the context engineering layer — retrieval, ranking, compression, and memory — that determines what makes it into a model call.
- Integrate and benchmark new foundation models as they become available; make principled decisions about model selection across agents based on capability and cost.
- Build user-facing surfaces — playgrounds, agent traces, control panels — and ship them to production.
- Collaborate closely with product to take new agent concepts from early brief to working v1 in weeks.
Benefits
- Health, dental, and vision care for you and your family (100% coverage for employee)
- Top-tier 401(K) plan with company matching
- Paid time off and paid holidays
- FSA, HSA and commuter benefits programs
- Team activity budget
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
