Senior Software Engineer, AI DevEx

Splash Sports

6d•$150,000 - $190,000•Remote

About The Position

Splash brings people and communities together through the gamification of live sports and events. We nurture, foster, and inspire the competitive spirit that lives within us all - one season, one game, one play at a time. With a variety of sports categories and pool formats to choose from, our websites are the premier spots for hosting friendly competitions against friends and family. We're a small, quickly growing, and remote-first team, looking for talented people who love sports and tech startups! The Role We're hiring an engineer to build the infrastructure that lets AI agents do most of our software development. It's our software factory: a ticket, bug report, support chat or a Datadog alert becomes work an agent picks up, builds, tests and gets reviewed. Engineers set the principles and the architecture and agents write, test and deliver the code under a continuous feedback loop. Location: This is a full-time, remote position in the US. Our team is distributed across the US and Prague. What You'll Ship Cloud coding environments. Any engineer or agent can spin up our core services in a environment and run their tests, without the local setup our polyrepo needs today. Autonomous coding agents. Agents running in those environments take tickets all to reviewed pull requests, with their own browser / native app testing, validation against production observability and configuration, fit with product requirements and compliance rules. SRE integration. Agents wired into Datadog and our incident tooling, so a production alert can create a fix PR. An agent platform for the business. The same runtime, triggers and guardrails, so teams outside engineering can run agents on it with help from our enablers. We'll judge the impact on two numbers: PR cycle time and review latency: how long work waits between opened and merged. Agent share of work: the percentage of PRs that agents author or review. What You'll Own Environments. Our local dev stack and cloud coding environments, reproducible from a fresh checkout by a person or an agent. Agents, built or bought. Pick the right agent for each job, whether that's an open-source agent running on our infrastructure or a vendor's cloud agent. Then wire it in: how it gets triggered (Slack, Jira, GitHub, Datadog), what credentials and context it gets, and how we see what it did and what it cost. Guardrails. Which data agents can touch, how secrets and PII are handled, and where human review is required for a company that runs real-money contests in a regulated industry. Feedback loops. Find where agents struggle in our codebases and fix the root cause, whether that's missing context, a flaky test, missing tools, or an environment gap.

Requirements

You do 90% or more of your work with AI agents today (Claude Code, Codex, Cursor, or similar).
Experience with multi-agent or subagent setups, orchestrating parallel agents or delegating work to subagents.
Infrastructure depth: AWS (ECS/Fargate, RDS, Lambda, networking and IAM), infrastructure as code (CDK/CloudFormation or Terraform), containers, and CI/CD pipelines.
Comfortable contributing directly to TypeScript/Node services.
Experience building internal platforms, dev environments, or developer tooling that engineers adopted.
Familiarity with evaluating agents for coding and non-coding tasks.
Ability to work independently in a remote team, communicate clearly across time zones, and proactively solve problems.
6+ years of software engineering experience, with meaningful time on infrastructure, platform, or developer tooling.

Nice To Haves

Experience with sandboxed or ephemeral environments at scale (Docker, devcontainers, Kubernetes, Nix, or similar).
Experience building MCP servers or other integrations that give agents access to real systems.
Experience with tracing and evaluations for agent work (OpenTelemetry, LLM traces, cost tracking).
Experience in a regulated industry like gaming or fintech.
A love for sports.

Responsibilities

Build the infrastructure that lets AI agents do most of our software development.
Create cloud coding environments where engineers or agents can spin up core services and run tests.
Develop autonomous coding agents that take tickets to reviewed pull requests, including testing, validation, and compliance.
Integrate agents with SRE tooling like Datadog and incident management systems.
Build an agent platform for business teams outside of engineering.
Own environments, including local dev stack and cloud coding environments.
Select, integrate, and manage AI agents (open-source or vendor).
Define and implement guardrails for agent data access, secrets handling, and human review requirements.
Establish feedback loops to identify and fix root causes of agent struggles in codebases.