We are seeking a senior Platform & Security Lead to own the technical foundation of our product: our cloud platform, its cost, and its security. Our radar-based medical devices provide real-time analytics to healthcare customers, running on a cloud platform built on AWS and Kubernetes, while our ML team trains and deploys models on Azure. As we scale, cost efficiency and security are becoming central to our business.

This is not a role where tasks are handed to you. You will identify what needs to change, weigh the options, decide, and see the decisions through, with much of the routine execution done by AI agents operating within the processes and guardrails you define. You will work directly with the CTO, take part in backend and ML design decisions, and be accountable for the platform’s reliability, security, and cost.

Key Responsibilities:

- Own the platform roadmap across AWS and Azure: decide what to improve, in what order, and why, and communicate the trade-offs behind your decisions.
- Own cloud cost: define how we measure it (unit economics rather than totals), decide where to invest and where to cut, and lead build-vs-buy and hosting decisions as we scale.
- Own security for our cloud, data, and internal systems: decide which risks matter most, fix root causes rather than symptoms, and turn compliance findings into lasting improvements.
- Represent security in customer reviews and audits, judge when we need external expertise such as penetration tests, and coordinate it.
- Define how AI agents operate our infrastructure: what they may do autonomously, what requires human approval, and how their actions are verified and audited.
- Decide what we monitor and alert on,



based on what matters to customers, and set up an on-call process our backend engineers can run.
- Define our resilience strategy, including availability zones, multi-region, and disaster recovery, with recovery objectives based on business needs and regularly tested.
- Simplify our infrastructure and delivery pipelines. We value removing complexity as much as adding capability.
- Challenge and contribute to backend and ML design decisions with operational, cost, scaling or security implications.
- Over time, support our ML engineers with infrastructure for data, training and model deployment.
- Document decisions and their rationale so the team can operate and understand why things are the way they are, without depending on any single person.

Key Requirements:

- Significant experience (typically 8+ years) designing and operating production systems on AWS, with deep hands-on Kubernetes (EKS) expertise.
- A proven track record of ownership: you can point to platform decisions you made yourself, the alternatives you rejected and why, and how the outcomes turned out, including decisions you would make differently today.
- Solid fundamentals in networking, Linux, distributed systems and cloud security. You understand why systems behave the way they do, not just how to configure them.




- Hands-on cloud security experience: identity and access management, network security, encryption, secrets management and vulnerability management, with experience in audits or compliance frameworks.
- Measurable results in cost optimization, and comfort reasoning quantitatively about cost, capacity and trade-offs.
- Extensive use of AI tools in your engineering work, grounded in the expertise to judge their output: you know what correct looks like, catch subtle errors, and could do the work yourself.
- Proficiency in Python and the ability to read and contribute to backend code.
- Experience with infrastructure as code (Terraform/OpenTofu), GitOps and CI/CD on production systems.
- Experience running production systems with on-call responsibility, incident response and postmortems that led to lasting improvements.
- Excellent written communication in English, including the ability to explain complex trade-offs concisely to technical and non-technical stakeholders.

Nice-to-Have:

- Experience in regulated industries such as healthcare, medical devices or fintech, or with frameworks such as ISO 27001 or SOC 2.
- Experience with Azure, especially Azure ML, and with ML data tooling such as DVC.
- Experience with realtime, streaming or IoT systems.
- Experience designing multi-region architectures or running Kubernetes on bare-metal or hybrid infrastructure.
- Experience operating infrastructure with AI agents, including defining permissions and guardrails.

Application Question(s):

- This is an on-site job. Are you comfortable relocating to Bhubaneswar?

Work Location: In person

📌 Platform & Security Lead (Bhubaneswar)
🏢 Sleepiz India
📍 Bhubaneswar