Senior AI Systems Engineer, Kindo
Agentic Platforms
$170-220k
+ Equity
Workflow automation & data security
Be an early applicant
Workflow automation & data security
21-100 employees
Be an early applicant
$170-220k
+ Equity
21-100 employees
Company mission
To provide the tools, security and support needed to manage AI across workforces.
Role
Who you are
- Have built and operated complex backend or distributed systems in production
- Have built LLM-powered or AI-native systems beyond demos, with real users and real constraints
- Have strong judgment around reliability, security, observability, and failure modes
- Are comfortable operating in ambiguous frontier areas and validating ideas through rapid iteration
- Use AI as a core part of your development workflow, not as an occasional convenience
- Operate with high ownership and autonomy and take systems end-to-end
- TypeScript required, Python strongly preferred
- Strong SQL proficiency
- Experience with production infrastructure; Docker/Kubernetes experience is a plus
- Familiarity with enterprise security patterns is a plus
- Domain familiarity with DevOps, SecOps, or infrastructure automation is a plus
What the job involves
- The role of the software engineer is changing. Autonomous agents can now execute real workflows, operate infrastructure, and improve over time. The hard problems are shifting from model demos to production systems: orchestration, memory, reliability, control, and security
- Kindo is an agent automation platform for DevOps and SecOps teams. We help organizations automate high-friction operational work using autonomous agents that run reliably, securely, and at scale. Our platform supports deployment on-prem, in hybrid environments, or in the cloud, with enterprise-grade security controls from day one
- We’re a small, highly technical team with strong customer traction and real enterprise revenue. Engineers have direct ownership over critical systems and shape how the platform evolves
- You will design, build, and operate core systems that enable autonomous agents to function reliably in production
- This is applied systems engineering with AI at the center, not ML research and not chatbot wrappers
- You’ll build production-grade agentic workflows, retrieval and memory systems, multi-model execution, and tool-calling integrations that interact safely with enterprise systems
- This is also frontier work
- Many of the patterns for agentic systems are still emerging
- You’ll explore new approaches, prototype quickly, and turn what works into durable production systems
- At the same time, strong distributed systems fundamentals still apply
- These systems must be reliable, secure, observable, debuggable, and maintainable under real-world conditions
- Agent execution systems, including autonomous task loops, scheduling, triggers, and control planes
- Retrieval and memory architectures, including context management, long-term memory, and structured memory
- Multi-model routing and orchestration across providers, balancing quality, latency, cost, and failure modes
- Tool-calling and integration frameworks for safe interaction with external services and enterprise environments
- Reliability, security, and operability foundations, including evaluation, observability, failure isolation, and recovery paths
- AI is a first-class tool in how we engineer
- You use AI across design, prototyping, implementation, testing, debugging, and incident response, and you continuously refine workflows that increase leverage without sacrificing quality
- You pair that velocity with discipline: guardrails, verification, and architectural boundaries that keep systems safe as autonomy increases
Application process
- Your work. A portfolio, demo, GitHub profile, blog post, recorded walkthrough, or any evidence of AI systems you’ve built. We want to see how you think, not just what you’ve done
- A brief note on what excites you about agentic systems and where you think the hard problems are
- Your resume, but know that the first two items matter more
- We’ll move fast. The interview process is designed to see how you actually work, not quiz you on trivia
Our take
Kindo is making AI safer for adoption by enterprises. In the past, third parties would have to aggregate cloud apps and centralise control of AI on behalf of a company wishing to use the software, wasting time and leading to potential security breaches. Through Kindo, customers can customise and centralise control of AI software themselves.
Kindo’s solution is an API that gives enterprises the freedom to manage AI across their entire workforces, while keeping the software centralised and compliant with regulations. Kindo claims that all AI models are supported on its platform, and deploys enterprise-level security in-house and in the cloud.
With a surge in companies using AI, Kindo’s product offers a new level of agency for companies hesitant to let third-party software into its systems. It's unsurprising that investors have been attracted to Kindo, which has used funding to enhance its systems and embark upon further R&D.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Jul 2024
$20.6m
EARLY VC
Sep 2023
$7m
SEED
Total funding: $27.6m
Company benefits
- Equity package
- Comprehensive health, dental, and vision insurance
- Unlimited vacation and paid time off policies
Company HQ
Little Tokyo, Los Angeles, CA
Leadership
Tony Wong
(SVP & Co-founder)Previously VP of Product at Upside.gg, Founder at Applied Agile and Digital Onion, and was an Agile Organisational Designer at Splunk.
Ron Williams
(CEO & Co-founder)Also the Limited Partner at First Close Partners. Previously Investor at Andela, Investor at Flutterwave and Seed Investor at Coily.
Charlie Hulcher
(Head of Technology & Co-founder)Previously Software Engineer at OpenSea, Senior Distributed Systems Engineer at Subspace, Engineering Manager at Bird and was CTO of UpChannel.
Bryan Vann
(CTO & Co-founder)Was a Senior Engineering Director at Google alongside a number of other roles there. Was also a Software Consultant at Clutch Legal Staffing and an Extreme Blue Engineering Intern at IBM.
Salary benchmarks
We don't have enough data yet to provide salary benchmarks for this role.
Submit your salary to help other candidates with crowdsourced salary estimates.
Share this job
View 3 more jobs at Kindo