Sr. AI Engineer

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About Commvault Commvault (NASDAQ: CVLT) is the gold standard in cyber resilience. The company empowers customers to uncover, take action, and rapidly recover from cyberattacks – keeping data safe and businesses resilient. The company’s unique AI-powered platform combines best-in-class data protection, exceptional data security, advanced data intelligence, and lightning-fast recovery across any workload or cloud at the lowest TCO. For over 25 years, more than 100,000 organizations and a vast partner ecosystem have relied on Commvault to reduce risks, improve governance, and do more with data.

Senior AI Engineer

The senior-most builder. You own the platform every other AI engineer builds on — architecture, roadmap, and the reference code, written by you.

01 The role

You are a Senior-level individual contributor - no direct reports. You lead through architecture and code, not

through a team. You own the shared platform the rest of AI Engineering builds on: the agent runtime, the

orchestration framework, the shared services, the golden paths, and the standards everyone codes against.

You set technical direction by shipping reference implementations, not slide decks. When a hard problem shows

up — a new agent pattern, a scaling wall, a reliability gap — you are the one who prototypes the answer and turns

it into something the team can reuse.

02 What you’ll own

▪ Own the platform architecture end to end - agent runtime, orchestration, shared services, and the abstractions

that let every other engineer move fast without reinventing the core.

▪ Own the technical roadmap - sequence the platform work, make the build-vs-buy calls, and defend the tradeoffs

to engineering and business leadership.

▪ Write the reference implementations - the first real version of each new capability, production-grade, that the

team then extends and specialises.

▪ Set and enforce standards - coding, evaluation, security, cost, and observability. You codify them as libraries and

templates, not documents nobody reads.

▪ Solve the hardest problems personally - scaling limits, non-deterministic failure modes, latency and cost ceilings,

cross-agent coordination.

▪ Design for safe autonomy at platform level - guardrail primitives, approval-gate patterns, and hard limits that

every agent inherits by default.

▪ Raise the engineering bar - review the critical designs and PRs, mentor through code, and make the strong

engineers around you stronger. Influence, not authority.

▪ Tie the platform to business outcomes - faster delivery, lower run-cost, higher reliability - and report the

leverage the platform actually created.

03 What you bring

▪ Deep fundamentals - algorithms, data structures, distributed systems, and system design at a level you can

defend under pressure.

▪ A track record of owning platforms or frameworks that other engineers built on - not just features.

▪ Production AI depth - you have shipped LLM/agent systems to real users and operated them, not just

prototyped.

▪ The judgement to say no - you kill complexity that will not pay off and keep the platform simple enough to

maintain.

▪ Influence without a title - you align senior engineers through the quality of your thinking and your code.

▪ Intellectual honesty about AI limits and patience with non-determinism - you engineer around failure modes

systematically.

▪ Clear executive communication - you make architecture and tradeoffs legible to non-technical leadership.

04 The stack

Core Engineering

• Must have Deep OOP (Python, C# or Java), REST & event-driven API design, async & concurrency, Azure Functions / App Service (or GCP / AWS equivalent), Service Bus, SQL & data modelling, Git
• CI/CD, testing, …