Staff Engineer, Karlo Platform

Kargo

New York (NY)

On-site

USD 200,000 - 220,000

Full time

14 days+

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Job summary

Kargo's AI Platform Engineer role on the Karlo Platform team focuses on owning the shared infrastructure powering agentic ad campaigns. You will ensure reliable, scalable hosting on LangGraph, build an evaluation framework, and deliver shared services and developer tooling to empower agent teams.

Responsibilities include memory management, observability, and SDKs/docs, with strong collaboration to translate needs into platform capabilities while maintaining security and reliability standards.

Qualifications

7–10 years of software engineering with 2+ years in production AI or agentic systems.
Deep hands-on LangGraph experience in production and related tooling.
Expertise in agentic design patterns and multi-agent orchestration.
Strong LLM foundations: prompts, memory, cost optimization, RAG.
Experience with LLM evaluation methodologies and production observability.
Backend fundamentals across distributed systems, API design, event-driven arch.
Experience building shared platform infrastructure and SDKs/documentation

Responsibilities

Own and harden LangGraph-based hosting infrastructure for all agent teams.
Design a shared evaluation framework to validate correctness and catch regressions.
Ship production-ready shared services: auth, billing, and integrations.
Own checkpointing and memory management across long-running conversations.
Instrument end-to-end observability: tracing, latency, cost, failures.
Build SDKs, docs, and onboarding tooling to shorten ramp time.
Collaborate with agent teams to translate needs into platform capabilities.

Skills

LangGraph production

LangChain ecosystem

Agentic design patterns

LLM foundations

LLM evaluation & observability

Distributed systems

TypeScript

Golang

Cloud infrastructure

CI/CD

SDKs & docs

Education

B.S. or higher in CS/Engineering/Math

Tools

LangChain

LangSmith

AWS

GCP

Azure

Docker

CI/CD

Job description

Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our dynamic teams work to radically raise the bar on what agentic AI, CTV, eCommerce, social, and mobile can do to deliver unique ad experiences across the world’s most premium platforms. Taking a Creative Science approach to all we do, we continuously innovate solutions that outperform industry benchmarks and client expectations. Kargo is growing rapidly and currently has offices in NYC, Chicago, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland.

Who We Hire

Techies who want to build the future. Creatives who want to design it better. Communicators to win business. Collaborators to build it. Data pros who turn numbers into insights. Product builders who turn ideas into innovations. Anyone eager to be on a team that doesn’t stop to ask what’s next, because they’re already building it.

The Opportunity

Karlo is Kargo's agentic ad-buying platform, where customers use conversational AI agents to build campaigns, creatives, targeting strategies, and analytics. As an AI Platform Engineer on the Karlo Platform team, you'll own the shared infrastructure every agent runs on — observability, model evaluation, the LangGraph runtime, checkpointing and context memory management, shared services, and the developer experience tying it all together. Your goal is to make the platform invisible to the agent teams building on it: so reliable, scalable, and well-documented that they can focus entirely on their agents.

The Daily To-Do

Own and harden the core LangGraph-based agent hosting infrastructure so every agent team can build and deploy with confidence — no undocumented behaviors, no surprise failures
Design and deliver a shared evaluation framework that lets agent teams validate correctness, measure quality, and catch regressions before they reach customers
Ship production-ready shared services — authentication, billing, and integration layers including Salesforce and CXP — that agent teams consume cleanly instead of rebuilding
Own checkpointing and agent context memory — state persistence, history compaction, and retrieval of relevant prior context across long-running, multi-turn conversations
Instrument the platform end-to-end: every agent, every session, every failure, with tracing across LLM calls plus latency, cost, and failure-mode visibility
Build the SDKs, documentation, and onboarding tooling that cut a new agent team's ramp time from weeks to days
Partner closely with agent teams to translate their needs into platform capabilities, and measurably reduce the infrastructure overhead they carry today

Qualifications

7–10 years of software engineering experience, including at least 2 years building production AI or agentic systems — shipped and operated, not prototyped
Deep hands-on experience with LangGraph in production: graph construction, node and edge design, conditional routing, state management, and agent lifecycle management; plus the broader LangChain ecosystem and LangSmith for tracing, evaluation, and dataset management
Command of agentic design patterns — ReAct, Plan-and-Execute, multi-agent orchestration, human-in-the-loop workflows, and tool use — with experience operating multi-agent systems and state handoff across agent boundaries
Strong LLM foundations: prompt engineering, context window management, memory architectures for multi-turn agents, token and cost optimization, RAG architectures (vector stores, embedding pipelines, retrieval, reranking), and model selection tradeoffs
Experience with LLM evaluation methodologies and production observability for AI systems, including the ability to debug non-deterministic agent behavior methodically
Strong backend fundamentals across distributed systems, API design, and event-driven architecture; TypeScript required and Golang a strong plus; cloud infrastructure (AWS, GCP, or Azure), containerization, and CI/CD
Experience building shared platform infrastructure consumed by multiple teams, with a track record of improving developer experience through SDKs, documentation, or internal tooling; B.S. or higher in Computer Science, Engineering, Mathematics, or equivalent practical experience; AdTech or programmatic experience a plus

In accordance with applicable federal, state, and local pay transparency laws, the anticipated base salary range for this position is listed below. In addition to base salary, this role is eligible for variable compensation — either the Kargo Sales Incentive Plan (sales roles) or an annual discretionary bonus (all other roles). Actual compensation may vary based on factors such as geographic location, work experience, education, and skills.

U.S Salary Range: $200,000 — $220,000 USD

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