Senior Software Engineer, Internal Tools & Automation

Tatari

$160K — $180K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in cloud-based infrastructure or developer tooling roles; AWS preferred
  • Hands-on experience with AI coding assistants in daily workflow
  • Proven experience with LLM APIs and agentic workflow design
  • Track record of improvement in CI/CD systems, build/test infrastructure
  • Strong Python and shell scripting skills
  • Experience with container orchestration (Kubernetes, Docker)
  • Familiarity with infrastructure-as-code, preferably Terraform

Responsibilities

  • Own strategy, roadmap, and execution for developer experience and AI tooling
  • Evaluate and deploy AI coding assistants across engineering teams
  • Design and build AI-powered agents for engineering workflows
  • Identify and eliminate friction in the development inner loop
  • Create ephemeral developer environments for microservices
  • Define and measure developer productivity metrics
  • Collaborate closely with application engineers and data scientists

Benefits

  • Equity compensation
  • Health insurance for you and your dependents
  • 401K, FSA, and commuter benefits
  • $150 monthly spending account
  • $1,000 annual continued education benefit
  • Unlimited PTO and sick days
  • Monthly Company Wellness Day Off
  • Snacks, drinks, and catered lunches
  • Team building events
  • Hybrid work model with 2 days in office
Full Job Description
We are looking for a Senior or Staff engineer to join engineering at Tatari, working closely with the SRE team, and lead how Tatari's engineers build software. Every hour an engineer spends fighting a slow CI pipeline, a flaky test, a confusing deploy, or a manual process is an hour not spent shipping product. The arrival of AI coding tools has made the gap between a great developer experience and a mediocre one wider than ever. You will own that gap. You will drive the strategy and hands-on execution for developer experience and AI tooling across our engineering organization: evaluating and rolling out AI coding assistants, building internal LLM-powered agents and automations, bringing ephemeral developer environments to our microservice landscape, speeding up the edit-build-test-deploy loop, and measuring the impact of all of it. You'll work from a foundation of solid infrastructure engineering, and occasionally contribute to core reliability and infrastructure work, but the majority of your time is spent making Tatari's engineers (human and AI alike) faster and happier. Working with a small team, this job affords a lot of agency and the opportunity to work with users across application engineering, data science, and analytics. Responsibilities • Own the strategy, roadmap, and execution for developer experience and AI tooling across Tatari engineering • Evaluate, deploy, and drive adoption of AI coding assistants and agentic development tools across the engineering org including enablement, best practices, guardrails, and cost management • Design and build internal AI-powered agents and automations for engineering workflows: CI failure triage, incident response tooling, code review assistance, operational runbooks, and internal bots • Identify and eliminate friction in the development inner loop: CI/CD pipeline speed and reliability, build and test infrastructure, local development environments, and deployment workflows • Design and implement ephemeral developer environments across our microservice landscape: on-demand, production-like environments for developing, testing, and previewing changes • Define and instrument developer productivity metrics (DORA-style delivery metrics, AI tooling adoption and impact) and use them to prioritize where the leverage actually is • Partner with application engineers, data scientists, and analytics teams by sitting with them while they work, learning their current process firsthand, and turning what you observe into improvements they will actually adopt • Participate in technical architecture discussions Qualifications • 5+ years of experience in cloud-based infrastructure, platform, or developer tooling roles (AWS preferred); for Staff level, a track record of driving tooling or platform adoption across multiple teams • Daily, hands-on use of AI coding assistants (Claude Code, Cursor, Copilot, or similar) in your own workflow, with informed opinions about where they create leverage and where they don't • Experience building with LLM APIs and agentic workflows (function/tool calling, MCP, prompt design, or agent frameworks) • Experience owning or significantly improving CI/CD systems, build/test infrastructure, or developer environments, with measurable results • Strong Python and shell scripting skills • Experience with containerization and orchestration (Kubernetes, Docker, or similar) • Experience with infrastructure-as-code (Terraform preferred) • Empathy for the frustrations and toil that slow engineering teams down and an intrinsic drive to fix them Nice to have • Experience running an AI tooling rollout or enablement program at a previous company • Experience with LLM evaluation approaches for internal tooling (measuring quality, not just adoption) • Experience building ephemeral or preview environments (per-PR deployments, namespace-based isolation, sandboxes) in a microservice architecture • Go or Rust • Experience with GitHub Actions at scale, build caching, or test parallelization/flake management • Experience managing RDBMS (Postgres/RDS, Redshift, or similar) and data infrastructure Benefits • Total compensation ($160,000-180,000/Annually) • Equity compensation • Health insurance coverage for you and your dependents • 401K, FSA, and commuter benefits • $150 monthly spending account • $1,000 annual continued education benefit • $500 Newbie Productivity Perk • Unlimited PTO and sick days • Monthly Company Wellness Day Off • Snacks, drinks, and catered lunches at the office • Team building events • Hybrid RTO of 2 days per week in office #LI-HYBRID

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