Location : Bengaluru, India · Full-time
About Disseqt
Disseqt is the assurance layer for enterprise AI governance - helping organizations test, protect, and deploy responsible AI at scale. We're building the infrastructure that makes AI governance real, not shelfware. As we scale rapidly, we're looking for a hands-on engineering leader to own the foundation we are building on.
The Role
You'll own everything that keeps Disseqt running, scaling, and shipping fast. Infrastructure, platform tooling, delivery pipelines, ML infra, data infrastructure, cloud costs and the ability to scale all of it as we grow. This is a player-coach role: you'll lead a lean team but stay deeply hands-on.
What You'll Own
Cloud Infrastructure - Design, build, and operate our cloud environment (AWS/GCP). Reliability, scalability, and cost efficiency are your north star
ML & AI Infrastructure - Model serving, inference optimization, vector databases, GPU resource management, and MLOps pipelines
Data Infrastructure - Own the data platform layer: pipelines, storage, lakehouse architecture, real-time streaming, and data reliability. Ensure data flows cleanly across our AI and product stack
Platform Engineering - Internal developer platform, Kubernetes, CI/CD tooling, and developer experience
Delivery Pipelines - Enterprise-grade release pipelines, deployment automation, and environment management
DevSecOps - Security embedded into every pipeline and infrastructure layer not bolted on
Scale & Reliability - Design for scale from day one. SLO definitions, SRE practices, incident response, and the ability to go from startup to enterprise-grade without rebuilding everything
Cost Engineering - Cloud spend ownership, FinOps practices, resource optimization
What We're Looking For
10+ years in infrastructure, platform, or DevOps engineering - with at least 2–3 years in a leadership role
Deep hands-on experience with Kubernetes, Terraform, and major cloud platforms (AWS/GCP)
Built or operated ML infrastructure - model serving, MLOps pipelines, GPU infra
Experience building and operating data infrastructure at scale - pipelines, streaming (Kafka/Flink), data lakes, or warehouse tooling
Strong CI/CD and delivery pipeline experience at scale
Proven track record of scaling systems - you've taken infrastructure from early-stage to high-throughput production
Security-first mindset - DevSecOps is second nature
Cloud cost management - you've owned a budget and optimized it
Startup experience preferred - comfortable with ambiguity and building from scratch
Excellent communicator - can translate infra complexity to product and business stakeholders
Nice to Have
Experience with AI governance, compliance, or regulated enterprise environments
Familiarity with LLMOps and agentic AI deployment patterns
FinOps certification or equivalent hands-on cost engineering experience
Why Disseqt
Greenfield infra - build it right from the start
AI-era problems - GPU clusters, inference pipelines, agent deployment, data at scale
Lean team, high ownership
Backed by a mission: Ship Responsible AI
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