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About This Role
As the global leader in high-speed connectivity, Ciena builds the critical infrastructure powering the AI era. We’re a technology company shaping the future of networking, guided by innovation, integrity, and collaboration. Through development opportunities, meaningful work, and flexibility, Ciena supports growth and well-being—on and off the job. Connect with a career that matters.
The Principal, Sales - Cloud & AI Components will be responsible for driving growth in Ciena's global semiconductor business through both direct and indirect sales channels within the Cloud & AI market. This role reports directly to the Global Leader, Global Cloud & AI Networking Sales.
Ciena's Cloud & AI business segment is supported by the Global Cloud Networking Sales organization and serves hyperscale, neocloud, native AI, emerging AI, data center, and related customers globally.
The successful candidate will lead direct sales engagements with targeted customers while partnering closely with direct sales teams, Product Line Management (PLM), R&D, and ecosystem partners to drive adoption of Ciena's interconnect solutions.
The ideal candidate will have a strong background selling semiconductor and component solutions into hyperscale environments, with experience positioning high-performance electro-optic assemblies and modules across data center, switching, routing, and optical transport applications. The candidate must demonstrate the ability to work cross-functionally with Product Line Management, Engineering, Marketing, Legal, Sales, Finance, and Services organizations to execute successful sales strategies within the assigned market and territory.
This individual will regularly engage with executive-level prospects, customers, and partners and will be expected to leverage an established industry network to create new business opportunities. The ability to anticipate market trends and understand evolving dynamics across hyperscale, AI, data center, OEM, and ODM segments is highly desirable.
This role requires strong leadership, influence, and collaboration skills to drive success both internally and externally.
Key Responsibilities
Business Development & Sales Execution
- Develop and execute strategies to market and sell Ciena's components portfolio directly to targeted customers.
- Create and execute business plans that support sales growth within priority accounts and market segments.
- Drive sales of electro-optic assemblies, modules, and intellectual property into: Data center environments Semiconductor manufacturers and adjacent markets OEM and ODM partners Related ecosystem participants
Sales Leadership
- Consistently exceed sales targets across assigned accounts and market segments.
- Apply complex sales methodologies with comprehensive stakeholder engagement and account planning.
- Maximize utilization of Ciena's interconnect solutions and related intellectual property portfolio.
- Maintain clear and accurate reporting on direct and indirect sales strategies, opportunities, and progress.
Cross-Functional Collaboration
- Promote collaboration across Product Line Management, R&D, Marketing, Services, Commercial Management, Legal, Human Resources, and other corporate functions.
- Utilize sales and business tools effectively, including: Salesforce CRM Bid management applications Contract Lifecycle Management (CLM) tools
- Ensure compliance with all company sales policies, procedures, and guidelines.
Travel
- Approximately 35% travel required.
Required Experience
The ideal candidate will have a proven track record of:
- Building and executing business plans and sales strategies from the ground up within high-growth technology markets.
- Developing strong relationships with senior executives and key decision-makers across Cloud & AI organizations.
- Driving successful design wins and solution adoption within data center environments and through OEM/ODM channels.
- Demonstrating deep understanding of customer requirements and market dynamics within the data center and AI infrastructure ecosystem.
- Selling complex semiconductor, component, or electro-optic solutions into hyperscale and cloud customers.
Desired Leadership Attributes
- High integrity and transparency in business dealings.
- Strong collaboration and team-oriented mindset.
- Growth-oriented and entrepreneurial approach.
- Resilience and ability to thrive in dynamic market environments.
Education & Qualifications
- Bachelor's degree in a technical field preferred, or equivalent relevant experience.
- Minimum of 15+ years of direct hardware, semiconductor, or component sales experience.
- Extensive knowledge of: Electro-optic solutions Data center architectures Switching and routing platforms Optical transport technologies Cloud and AI infrastructure markets
This role is ideal for a seasoned sales leader with established hyperscaler relationships, deep semiconductor and optical networking expertise, and a passion for driving growth in the rapidly expanding Cloud & AI ecosystem.
The salary range for this position, in California, is:
$281,200.00 - $449,200.00 USD
#LI-JD
Pay ranges at Ciena are designed to accommodate variations in knowledge, skills, experience, market conditions, and locations, reflecting our diverse products, industries, and lines of business. Please note that the pay range information provided in this posting pertains specifically to the primary location, which is the top location listed in case multiple locations are available.
Non-Sales employees may be eligible for a discretionary incentive bonus, while Sales employees may be eligible for a sales commission. In addition to competitive compensation, Ciena offers a comprehensive benefits package, including medical, dental, and vision plans, participation in 401(K) (USA) & DCPP (Canada) with company matching, Employee Stock Purchase Program (ESPP), Employee Assistance Program (EAP), company-paid holidays, paid sick leave, and vacation time. We also comply with all applicable laws regarding Paid Family Leave and other leaves of absence.
At Ciena, we are committed to building and fostering an environment in which our employees feel respected, valued, and heard. Ciena values the diversity of its workforce and respects its employees as individuals. We do not tolerate any form of discrimination.
Ciena is an Equal Opportunity Employer, including disability and protected veteran status.
If contacted in relation to a job opportunity, please advise Ciena of any accommodation measures you may require.
Salary Context
This $281K-$449K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $176K across 1540 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Ciena, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $212,000 based on 11,857 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($365K) sits 72% above the category median. Disclosed range: $281K to $449K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Ciena AI Hiring
Ciena has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $449K - $449K.
Remote Work Context
Remote AI roles pay a median of $185,906 across 2,124 positions. About 6% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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