AI Solutions Engineer

Recruitment Fraud Alert 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.   What to know: * 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 [wwrecruitingteam@commvault.com]    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.  Clumio is bought by builders. The people who evaluate us are Staff engineers, SREs, platform leads, and directors of engineering—people who will decide whether to trust us with 50 petabytes of S3 before they ever talk to a salesperson. They arrive from a search result, an AI assistant, or a colleague’s recommendation. They open the docs. They start a trial. And within about twenty minutes, they either get their first backup running or they close the tab.  This role owns that twenty minutes—and everything that leads up to it.  You are not a documentation writer who sits downstream of engineering and turns release notes into paragraphs. You are a content engineer: you run the code, you build the example, you break the workflow, and then you write the thing that makes it obvious. Every guide you publish ships with something that actually works—a Terraform module, a CloudFormation template, a CLI walkthrough, a tested API call. If a builder can’t copy it, paste it, and have it succeed on the first try, it isn’t finished.  You will sit with the Cloud Native product organization and work shoulder-to-shoulder with engineering, product, and growth. Your work is the top of the funnel, the onboarding path, and the reason a trial converts.  Why This Role Matters  Clumio is one of the top products in AWS Marketplace and carries an NPS of 88, and we got there because builders tried it and it worked. But the ceiling on a product-led motion is set by how many people can succeed without us in the room—and right now, that ceiling is our content.  If you are the engineer who kept ending up writing the guide everyone linked to, or the writer who got tired of describing software you were never allowed to run—this is the seat where those are the same job.    What You’ll Do: Own the Content That Sells the Product  * Write and maintain the Clumio docs—getting-started paths, service-by-service protection guides, API and SDK references, restore and recovery runbooks—treating them as a product surface, not an archive  * Build the fastest possible path to first value: a builder should get their first S3 bucket, DynamoDB table, or RDS instance protected without opening a support ticket or booking a call  * Author deep technical guides on the workloads that define us—S3 at scale, Apache Iceberg and S3 Tables, DynamoDB, EC2/EBS, RDS/Aurora—including the hard parts: cost, scale, recovery time, and what happens when something goes wrong  * Own the technical narrative in AWS Marketplace listings, trial flows, and in-product onboarding copy  Build It Before You Write About It  * Ship and maintain working example repositories: Terraform modules, CloudFormation and CDK templates, scripts, and sample integrations that builders can fork  * Test every workflow you document in a real AWS environment—validate the code, validate the permissions, validate the failure modes  * Build the hands-on lab and GameDay content used at AWS events, where builders break something and recover it themselves  * Produce short technical demos and walkthroughs—written, visual, or recorded—that show the product doing the thing rather than describing it  Write for How Builders Actually Find Things  * Create content that ranks in search and—increasingly—gets retrieved and cited by AI assistants: specific mechanisms, worked examples, real numbers, and concrete scenarios rather than hedged feature claims  * Identify the questions builders are already asking about cloud data protection and answer them better than anyone else has  * Turn customer-scale reality into public proof: petabytes, object counts, recovery times, cost deltas  Close the Loop with Product and Growth  * Instrument and watch what your content does: activation rate, time to first backup, trial-to-paid conversion, docs-sourced signups, support deflection  * Bring friction back to engineering and product—when the docs have to apologize for the product, the product is the bug  * Partner with growth on onboarding experiments, and with field and partner teams so what you build for self-serve also arms sellers  What Success Looks Like  * Builders reach first value in a trial without human help, and the activation curve shows it  * Docs and guides are a measurable source of qualified signups, not a cost center  * Every AWS service Clumio protects has a current, tested, copy-pasteable guide—and the example repos actually run  * When an engineer asks an AI assistant how to protect S3 at scale, our content is what it draws from  * Support tickets that used to be “how do I…” questions stop arriving, because the answer is already published  Your First 90 Days  * Week 1: You run the trial yourself as a new user would, and write down every place you got stuck  * Day 30: You have shipped a rebuilt getting-started path and at least one tested example repo  * Day 90: You own the content roadmap, you have measurable movement on activation, and engineering comes to you before a feature ships—not after  What You Bring  * 4+ years in a developer-facing technical role—technical writing, developer relations, solutions engineering, support engineering, or software engineering with a strong writing track record  * You write code and you write prose, and you refuse to publish the second without validating the first  * Working fluency in AWS: S3, IAM, DynamoDB, RDS, EC2, and the mental model of how a cloud team actually operates  * Hands-on with infrastructure as code (Terraform, CloudFormation, or CDK), APIs, SDKs, and the command line  * Docs-as-code fluency: Git, Markdown/MDX, PR-based review, and content that lives next to the product  * The instinct of a teacher—you know where a reader will get confused before they do, and you write to that  * Demonstrated technical content that shipped and moved something: writing samples and example repos required  Nice to Have  * Background in data protection, storage, data engineering, or lakehouse architectures (Iceberg, Parquet, S3 Tables)  * Experience at a product-led company where docs were a growth channel with real targets attached  * AWS certification, or a personal AWS account with a billing history that tells a story  * Experience with docs analytics, search behavior, or optimizing content for AI retrieval    You'll love working here because: •    High income earning opportunities based on self-performance •    Employee stock purchase plan (ESPP) •    Continuous professional development, product training, and career pathing •    Generous global benefits   #LI-AM1 #LI-Remote Thank you for your interest in Commvault. Reflected below is the minimum and maximum base salary range for this role. At Commvault we use broad salary ranges in our job postings to reflect the diverse levels of expertise and experience among our candidates and is not reflective of the total compensation and benefits package. The specific salary offered will be determined based on your unique qualifications, including your relevant experience, skills, and the value you bring to the role. While the range provides a general idea of the compensation, it is important to note that placements within the range are not automatic and will be carefully considered to ensure a fair and competitive offer. We are committed to rewarding talent and experience. Pay Range $72,250—$155,250 USD Commvault is an equal opportunity workplace and is an affirmative action employer. We are always committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status and we will not discriminate against on the basis of such characteristics or any other status protected by the laws or regulations in the locations where we work. Commvault’s goal is to make interviewing inclusive and accessible to all candidates and employees. If you have a disability or special need that requires accommodation to participate in the interview process or apply for a position at Commvault, please email accommodations@commvault.com [accommodations@commvault.com] For any inquiries not related to an accommodation please reach out to wwrecruitingteam@commvault.com [wwrecruitingteam@commvault.com].   Commvault's Privacy Policy [https://www.commvault.com/privacy-policy]

At Locus Robotics, we build AI-powered systems and intelligent robots that keep global supply chains running. Our platform combines advanced AI, real-time decision-making, and autonomous robotics to help leading companies improve efficiency, scale operations, and adapt to constant change. Locus Robotics is a place to do meaningful work with real-world impact, where your ideas move quickly from concept to deployment. We invest in our people, encourage continuous learning, and give you the opportunity to grow your career while building technology that is used every day at global scale. The Technical Director, AI Enterprise Architect is a highly visible, hands-on individual contributor (IC) role with a direct mandate from the executive leadership team. As a strategic and technical leader, you will serve as a force multiplier across the organization, partnering with senior stakeholders to identify high-impact AI opportunities, translate complex business challenges into scalable AI-native solutions, and drive execution from concept through adoption. This is a rare opportunity to join one of the largest privately held robotics companies in the United States at the forefront of Physical AI. You will play a pivotal role in shaping and accelerating an enterprise-wide AI transformation initiative with full CEO and Board-level sponsorship. Working across business and technology functions, you will have significant influence over AI strategy, architecture, implementation, and measurable business outcomes—owning both the direction and the impact of the company's AI-first vision. This is both a strategy and build role - you will define the roadmap, architect the platform, and lead execution. Responsibilities Enterprise AI Transformation Strategy: Define and drive the company-wide AI roadmap, including prioritization frameworks, sequencing of initiatives, and executive alignment. Ensure a relentless focus on business outcomes rather than tool adoption. AI-Native Workflow Redesign: Partner with leaders across Sales, Customer Success, Finance, Operations, and Marketing to identify high-leverage opportunities. Redesign processes from the ground up into AI-native, automated workflows. AI Systems & Agentic Workflow Development: Design, build, and deploy production-grade AI systems, including agentic workflows that automate end-to-end processes. Own the full lifecycle—from scoping through deployment, monitoring, and iteration. LLM & Data Integration Architecture: Architect scalable LLM-powered systems, including retrieval-augmented generation (RAG), unified context layers, and integration frameworks that connect enterprise data sources. Data & Platform Engineering: Design and implement robust data pipelines, integration layers, and shared infrastructure that enable reusable, enterprise-wide AI capabilities. Ensure reliability, scalability, and accessibility across systems. AI Governance, Security & Standards: Establish frameworks for model governance, risk management, data access, and security. Define standards for tools, evaluation, and responsible AI usage. Technical Leadership & Culture Building: Drive AI adoption across the organization by mentoring leaders, establishing best practices, and fostering AI-native ways of working. Core Expertise * Deep expertise in modern AI techniques, including transformer architectures, multimodal systems, and LLM application design. Strong understanding of: Fine-tuning and adaptation (LoRA, PEFT, RLHF/DPO), RAG systems, embeddings, and tokenization and Prompt engineering and tool-augmented agents * Proven track record designing and operating production-grade AI systems that deliver measurable business impact (e.g., efficiency, revenue growth, cost reduction, user experience). * Experience embedding AI into core enterprise systems (CRM, ERP, knowledge systems, collaboration platforms) to enable end-to-end workflow transformation. * Strong grounding in: Data engineering (ETL/ELT, pipelines, APIs), Data architecture (Lakehouse, storage systems), Metadata systems (catalogs, lineage), Governance, security, and compliance frameworks Qualifications * Bachelor’s degree in Computer Science, Engineering, or a related technical field required; Master’s or PhD preferred * 5+ years leading enterprise AI or digital transformation initiatives, with demonstrated ownership of strategy through execution * 5+ years of hands-on experience in software engineering, data engineering, or AI/ML roles, with strong proficiency in Python and modern cloud platforms (AWS, Azure, or GCP) * Proven experience designing and deploying production-grade AI systems, including agentic workflows that automate end-to-end processes and drive measurable business outcomes * Deep expertise in LLM-based systems, including RAG architectures, prompt engineering, tool integration, and enterprise use of foundation models (e.g., GPT-4, Claude, or equivalent) * Strong foundation in data engineering and architecture, including ETL/ELT pipelines, APIs, Lakehouse environments (e.g., Databricks), and data quality/governance frameworks * Experience building scalable AI platforms including: Shared services, connectors, and agent frameworks, eEvaluation and observability tooling and deployment and scaling infrastructure * Ability to operate at both strategic and deeply technical levels- prototyping, architecting, and delivering complex AI systems in production environments. * Working knowledge of classical machine learning techniques (regression, classification, anomaly detection, time-series forecasting) and when to apply them vs. LLM-based approaches * Demonstrated ability to translate business problems into scalable technical solutions, with strong business acumen and outcome-driven thinking * Excellent English communication and leadership skills, with the ability to engage both technical teams and executive stakeholders and drive cross-functional alignment The expected base salary range for this role is $200,000 - $300,000 annually, based on external market data, plus bonus and equity.  Actual offers will depend on factors such as the candidate’s experience, education, training, key or critical skills, geographic location, and current market and business conditions Additional Information  Locus Robotics is an equal opportunity employer. Application Fraud Detection Notice: To help maintain a fair and secure hiring process, Locus Robotics may use AI-assisted and other automated tools to detect suspected fraud, misrepresentation, or misuse of the application process. Hiring decisions are not made solely by automated means unless otherwise disclosed where required by law.  It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.  Additional Information  Locus Robotics is an equal opportunity employer. Application Fraud Detection Notice: To help maintain a fair and secure hiring process, Locus Robotics may use AI-assisted and other automated tools to detect suspected fraud, misrepresentation, or misuse of the application process. Hiring decisions are not made solely by automated means unless otherwise disclosed where required by law.  It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.