SingleStore
About this role
SingleStore's AI Platform team builds the layer that lets customers run AI on their own data inside SingleStore Cloud: agent runtimes, tool integration, retrieval pipelines and the operations around them. The posting is careful to say this is not research, it is engineering heavy, and that you should understand AI/ML fundamentals well enough to make correct engineering decisions without being a researcher. Concretely, you build backend services for agent orchestration and tool execution, implement MCP style tool discovery so agents can call tools safely, design tenant aware and secure by default control plane APIs, and build the evaluation discipline: offline test sets, regression detection, prompt and model version tracking. Expect Go and Python on Kubernetes. Apply if you are a backend or distributed systems engineer who has picked up real AI platform work rather than an ML researcher looking for a product team.
Who this is for
Required by the posting: 4+ years of experience working on a SaaS product or production platform. Strong software engineering skills with experience in distributed systems, in Go, Python or similar. Experience building cloud native services covering Kubernetes, containers, service to service APIs and CI/CD. A solid understanding of AI/ML fundamentals, and the posting is explicit that you do not need to be a researcher but should understand the concepts well enough to make sound engineering decisions.
The real day to day: building and evolving backend services that power AI features, covering agent orchestration, tool execution, retrieval and RAG pipelines and model serving integrations; designing APIs and control plane workflows that are tenant aware, secure by default and observable; implementing MCP style tool discovery and integration so agents can safely call tools, connectors and internal services; engineering for reliability and scale including latency, cost controls, rate limiting, fallbacks, rollouts and incident readiness; establishing evaluation practice with offline test sets, regression detection, prompt, model and version tracking and quality gates; contributing secure by design AI work covering permissions, data access boundaries, prompt injection defences and auditability; and mentoring junior engineers.
Location and working pattern: listed as India, with the requisition in SingleStore's Hyderabad office.
Honest fit guidance: the phrase to take seriously is "this team is not pure research, it's engineering heavy". The hiring bar is distributed systems and cloud native services, with AI/ML understanding layered on top. If you have shipped production backend services and have taught yourself agents, RAG and evaluation properly, you are the target. If your AI experience is notebook and demo shaped, the reliability, multi tenancy and security requirements will be where it shows. Note also the security emphasis: prompt injection defence and data access boundaries are named requirements, not afterthoughts.
The real day to day: building and evolving backend services that power AI features, covering agent orchestration, tool execution, retrieval and RAG pipelines and model serving integrations; designing APIs and control plane workflows that are tenant aware, secure by default and observable; implementing MCP style tool discovery and integration so agents can safely call tools, connectors and internal services; engineering for reliability and scale including latency, cost controls, rate limiting, fallbacks, rollouts and incident readiness; establishing evaluation practice with offline test sets, regression detection, prompt, model and version tracking and quality gates; contributing secure by design AI work covering permissions, data access boundaries, prompt injection defences and auditability; and mentoring junior engineers.
Location and working pattern: listed as India, with the requisition in SingleStore's Hyderabad office.
Honest fit guidance: the phrase to take seriously is "this team is not pure research, it's engineering heavy". The hiring bar is distributed systems and cloud native services, with AI/ML understanding layered on top. If you have shipped production backend services and have taught yourself agents, RAG and evaluation properly, you are the target. If your AI experience is notebook and demo shaped, the reliability, multi tenancy and security requirements will be where it shows. Note also the security emphasis: prompt injection defence and data access boundaries are named requirements, not afterthoughts.
Apply on company site
Opens job-boards.greenhouse.io, the employer's own application page. Applying is always free.