Software Engineer - AI Automation & Agents

We’ve learned that scammers are impersonating Commvault team members—including HR and leadership—via email or text. These bad actors may conduct fake interviews and ask for personal information, such as your social security number.  

• Commvault does not conduct interviews by email or text.
• We will never ask you to submit sensitive documents (including banking information, SSN, etc) before your first day.

If you suspect a recruiting scam, please contact us at wwrecruitingteam@commvault.com 

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. 

We have an exciting opportunity to join our Business Technology Team! We are looking for a software engineer first—focused on writing clean code, designing robust systems, and delivering reliability at scale. You leverage AI to drive real business impact in two ways: building automation pipelines that ingest data, apply intelligence, and update downstream systems, and developing AI agents that reason, use tools, and take action. You move quickly to prototype and validate ideas, then harden solutions for production. You own the full stack end to end, including API design, cloud infrastructure, AI integration, business logic, evaluation, monitoring, and the feedback loops that continuously improve system performance. 

• →Re-engineer the process before automating it; map the workflow, cut the steps that shouldn't exist, then design the automation around the improved process, not the old one. 

• →Build end-to-end automation that connects business inputs - emails, documents, events - to outputs like classified data, routed records, and updated systems, through an AI processing layer. 

• →Design and build AI agent systems - from single-agent task executors to multi-agent pipelines where agents specialise, coordinate, and hand off. 

• →Design human-in-the-loop governance and guardrails - confidence thresholds, approval gates, escalation paths, and hard limits on what an agent may do unsupervised. 

• →Run AI operations - monitor for drift and hallucination, manage prompt and model versions, control token cost, and catch quality regressions before users do. 

• →Integrate Azure OpenAI and other LLM services into production - prompt design, context management, response validation, tool use, and function calling. 

• →Build RAG pipelines - ingestion, chunking strategy, embedding, vector store management, and retrieval tuning for real-world queries. 

• →Build and run the REST APIs and Azure services behind every pipeline, integrate enterprise systems (CRM, ERP, comms) via their APIs and standard protocols like MCP, and write the business-rule and validation layers on top of AI output. 

• →Tie every system to a business metric - productivity, cycle-time, or cost - instrument it, and report the impact you actually delivered. 

• Bachelor’s degree in Computer Science or related field
• 2–4 years of software engineering experience building production systems
• Strong fundamentals (algorithms, data structures, system design)
• Proficiency in Python, C#, or Java; experience building REST APIs
• Experience developing cloud-based applications (Azure preferred; AWS/GCP acceptable)
• Proven ability to deliver end-to-end solutions (design → deployment → support)
• Experience writing clean, maintainable, well-tested code

• Hands-on experience with LLMs (e.g., Azure OpenAI), including prompt design and output validation
• Experience building AI-powered workflows (automation pipelines, RAG, or similar)
• Familiarity with agent frameworks (e.g., LangChain, Semantic Kernel)

• Strong problem-solving skills and comfort with ambiguity
• Ability to communicate technical concepts clearly
• Self-starter with a learning mindset; adapts quickly to new tools and technologies
• Strong written and spoken English

• Vector DB internals, LLM observability, Fine-tuning, Multimodal AI, Salesforce / Dynamics 365 / Gainsight, Azure Data Factory, TypeScript / Node.js 

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