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About This Role
\**Senior Manager, Solution Marketing \- US Remote\**
About Axiom:
As the leading alternative legal services provider globally, Axiom gives in\-house legal teams on\-demand access to top legal talent and lawyers — deployed when, where, and how clients need it, for up to 50% less than national law firms. Axiom's network of 14,000\+ legal professionals includes 4,000\+ lawyers with Fortune 500 experience, delivering AI\-enabled legal services across more than 12 practice areas. Trusted by 75% of the Fortune 100 and thousands of mid\-market leaders, Axiom ranks \#1 among Alternative Legal Service Providers in 8 of 9 performance categories — including talent quality, breadth, productivity, and client experience — according to a top 5 global consulting firm. Across more than 3,000 engagements annually in 6 regions and 4 continents, 93% of clients rate Axiom lawyers as good as or better than top law firm attorneys, with 96% client satisfaction and measurable cost savings that reduce outside counsel spend without sacrificing quality. Stop overpaying for law firm work. Start with Axiom.
Overview:
As a Solution Marketing Senior Manager at Axiom, you will be pivotal in driving our Tech\+Talent 2026 vision forward. This remote role offers an exciting opportunity for a strategic thinker and marketer skilled in developing compelling value propositions for AI\-powered solutions that resonate deeply with diverse target audiences. By collaborating with cross\-functional teams, you will play a key role in executing our go\-to\-market strategies, enhancing our market presence, and boosting customer engagement.
For over 25 years, Axiom has been a trailblazer in the alternative legal services landscape, proudly serving more than 1,500 legal departments across the globe. We deliver a unique and innovative blend of world\-class legal talent and advanced AI tools, offering solutions that range from fully integrated project teams to individual secondments—uniting top\-tier legal talent with cutting\-edge technology. Our expertise spans 12 practice areas, empowering clients from Fortune 100 companies to SMBs to tackle complex legal challenges.
Join us to be part of a culture that celebrates collaboration, innovation, and success. Become a member of a forward\-thinking company that values creativity and strategic insight.
Key Responsibilities:
- Marketing Strategy Development and Execution:
- + Lead the development and execution of the Tech\+Talent 2026 marketing strategy to achieve key business objectives.
- + Utilize market research to identify trends, customer needs, and insights that shape and inform our marketing tactics.
- + Design and implement innovative marketing campaigns tailored to targeted customer segments, ensuring alignment with strategic goals.
- Solution Positioning and Messaging:
- + Develop clear and compelling solution positioning and messaging that differentiates Axiom's offerings with a specific focus on Axiom's AI capabilities.
- + Collaborate with strategy, technology, and commercial teams to convert capabilities into customer\-centric benefits and articulate these in marketing collateral.
- + Create engaging sales enablement materials, including solution briefs, presentations, and case studies to support sales efforts.
- Marketing Execution:
- + Drive the execution of our marketing plan for new solution launches, ensuring seamless integration across multiple digital channels.
- + Coordinate with marketing communications to deploy campaigns that drive brand awareness and increase demand generation.
- + Analyze marketing campaign performance and leverage data\-driven insights to refine and optimize strategies continuously.
- Cross\-Functional Collaboration:
- + Work closely with sales teams to capture customer insights and refine solution selling approaches.
- + Engage with strategy teams to deliver market feedback that guides prioritization of initiatives.
- + Collaborate with commercial teams to harness customer experiences in marketing narratives and success stories.
- Project Management:
- + Maintain detailed project plans, timelines, and documentation for marketing initiatives.
- + Identify and mitigate potential risks to ensure successful program delivery.
Success metrics
- Achievement of monthly and quarterly Tech\+Talent marketing goals.
- Increase in engagement with solution marketing content (website traffic, LinkedIn followers, email open and CTR, etc.).
- Timely and effective execution of marketing programs resulting in a high volume of client leads, wins, and referrals.
Qualifications:
- 7\+ years of experience in product marketing, solution marketing, or a similar role, ideally within the legal services, professional services, or technology sector.
- Strong understanding of B2B marketing dynamics and experience in implementing comprehensive marketing strategies.
- Demonstrated program and project management skills, with a track record of managing multiple campaigns and workstreams simultaneously.
- Exceptional communication and presentation skills, with the ability to convey complex ideas clearly.
- Proven success in developing and executing effective GTM strategies for tech\-based solutions.
- Strategic mindset with robust analytical and problem\-solving skills.
- Self\-motivated and capable of working independently in a remote environment while managing multiple priorities.
- Strong messaging capabilities, ideally with experience in legal industry marketing.
- Proficient with CRM applications (such as Salesforce.com) and marketing automation systems (such as HubSpot).
- Ability to translate strategic objectives into effective, market\-specific programs.
- Track record of driving results in a high\-growth, innovative, and fast\-paced environment.
- Legally eligible to work in the U.S.
- Bachelor's degree in marketing, business, communications, or a related field preferred
Characteristics:
- Proactive self\-starter, intrinsically motivated
- Intelligent, with strong critical thinking skills
- Ability to think strategically, paired with high attention to detail in execution
- Positive, can\-do attitude
- Ability to prioritize multiple projects simultaneously, naturally high RPM
- Strong interpersonal skills a must; values influencing \& building relationships
- Collaborative team player, yet also comfortable working independently
- Our People Reflect Our Values! We are:
- + Innovative: We generate new, creative, and disruptive ideas to change the status quo in their fields
+ Performance Oriented: We possess an unbelievable work ethic and unwavering commitment to quality
+ Cross\-functionally collaborative: We bring others together, creating strong relationships across lines of difference
+ Data \& Fact Based: We seek to understand and learn from information and perspectives everywhere
+ Customer First: We aim to delight our clients and legal talent at every opportunity
Axiom's total rewards philosophy is to be transparent and equitable with all job candidates. The annual base salary range for this role located in New York, Washington D.C., Philadelphia, and Boston is $111,000 \- $125,000 \+ a 20% annual bonus depending on experience. You can also participate in our benefits programs that include healthcare, life and disability coverage, 401K with company match, paid sick and personal time off, paid parental leave and more. Please note that the final compensation is determined by several considerations, including the quality of your experience and expertise, your ability to immediately contribute to Axiom, your potential to move up to the next level, the market you are located in, and other business considerations.
Accommodation for Individuals with Disabilities: Upon request and consistent with applicable laws, Axiom will attempt to provide reasonable accommodations for individuals with disabilities who require an accommodation to participate in the application process. To request an accommodation to complete the application form, please contact us at [email protected] and include "Applicant Accommodation" in the subject line.
Salary Context
This $111K-$125K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At AXIOM, 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($118K) sits 35% below the category median. Disclosed range: $111K to $125K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
AXIOM AI Hiring
AXIOM has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $125K - $125K.
Remote Work Context
Remote AI roles pay a median of $170,000 across 1,926 positions. About 15% 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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