Senior Competitive Intelligence Engineer

Accountabilities:

• Conduct hands-on technical evaluations of cloud and AI platforms by provisioning infrastructure, deploying workloads, measuring performance, and documenting findings in reproducible formats that enable reliable comparison and informed decision-making.
• Develop and manage a structured benchmarking framework for AI inference workloads, standardizing test conditions, models, metrics, and key performance indicators to support meaningful comparisons across providers and technologies, including models such as Llama and Mistral.
• Assess competitor architectures and technical capabilities across APIs, networking, storage, GPU availability, orchestration tooling, developer experience, and other relevant areas, while documenting actual product behavior and performance observed during deployment.
• Create technically rigorous battle cards, comparison guides, and enablement content for Sales and Presales teams, ensuring that competitive claims and differentiation are grounded in verified technical evidence.
• Partner closely with Product Management to evaluate cloud products, identify customer-relevant gaps and opportunities, translate technical findings into actionable recommendations, and influence future product roadmap priorities.
• Review and fact-check differentiation claims used in marketing materials, sales presentations, and analyst briefings, helping maintain technical accuracy, credibility, and consistency across external and internal communications.

Requirements:

• Bring at least 12 years of relevant technical experience in areas such as cloud engineering, solutions architecture, DevOps, technical marketing, or presales within enterprise technology, along with a Bachelor's degree or equivalent combination of education and experience.
• Demonstrate strong hands-on cloud infrastructure expertise, including the ability to provision compute resources, configure networking, deploy containers, troubleshoot performance issues, and independently investigate complex technical environments.
• Have practical experience operating AI/ML inference workflows, deploying model endpoints, measuring performance metrics, and understanding the cost structures associated with cloud-based AI workloads.
• Be experienced in designing reproducible technical tests, controlling variables, defining meaningful benchmarks, and presenting accurate results using sound benchmarking and experimentation methodologies.
• Possess the ability to translate complex technical findings into clear written content that engineers can trust and business stakeholders can act upon, while confidently presenting insights to diverse technical and professional audiences.
• Demonstrate a high degree of integrity and intellectual honesty, communicating competitive findings transparently and objectively while maintaining credibility and trust with internal stakeholders.

Benefits:

• Base salary of $139,300–$250,700 USD per year for U.S.-based candidates, with compensation determined by factors including relevant experience, skills, certifications, and location.
• Potential additional compensation through annual bonuses or incentives, equity awards, and an Employee Stock Purchase Plan (ESPP).
• Industry-leading healthcare benefits, with eligibility requirements applying.
• 401(k) savings plan to support long-term financial planning.
• Company holidays, paid time off, and sick time.
• Family-friendly benefits, including parental leave.
• Employee assistance resources with dedicated support for mental and financial wellness.
• Opportunities to develop new technical and professional skills through structured learning, mentoring, internal events, and digital learning resources.
• The opportunity to influence cloud and AI product evolution through hands-on technical investigation and cross-functional collaboration.
• Exposure to a broad range of cloud technologies, AI platforms, competitive architectures, product strategy, and enterprise go-to-market initiatives.