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Apply Now →About This Role
Lumenci is seeking a GTM \& Customer Success Lead – AI Platform to help launch, commercialize, and scale iLumos.ai across law firms, enterprise corporations, and litigation funders. This is a hybrid, customer\-facing leadership role that owns the customer journey from pre\-sales discovery through onboarding, adoption, renewal, and expansion, while helping shape go\-to\-market strategy for a next\-generation AI\-powered patent intelligence platform.
About Lumenci
Founded in 2018, Lumenci is a premier intellectual property consulting firm specializing in patent litigation, expert witness testimony, and patent monetization for leading corporations and global law firms operating across the software, telecommunications, semiconductors, and emerging technology sectors.
A key part of Lumenci’s model is the integration of deep technical expertise with litigation strategy. Our teams support high\-stakes disputes by developing technical narratives, performing rigorous analysis, and partnering with world\-class expert witnesses whose testimony shapes case outcomes in courts and arbitration forums worldwide.
Headquartered in Austin, Texas, with offices in San Francisco, New York, and Gurugram, India, Lumenci delivers end\-to\-end support spanning technical analysis, expert strategy, valuation, and monetization execution. Our differentiated approach, which includes combining engineering depth, litigation experience, and operational rigor, has resulted in long\-term partnerships with leading law firms and technology companies navigating complex IP disputes. Lumenci is backed by VSS Capital Partners (“VSS”) and Century Equity Partners (“CEP”). VSS is a private equity firm dedicated to investing in tech\-enabled business services, healthcare, and education companies. Since 1987, VSS has managed eight private capital funds with aggregate committed capital of nearly $4 billion across 103 platform companies and over 600 add\-on acquisitions.
VSS’s investment in Lumenci was from VSS Structured Capital IV, L.P. (“VSS SC IV”), a $530 million fund which had its final closing in December 2022\. CEP is a private equity firm headquartered in Boston, MA, that partners with companies seeking investments to support growth or fund acquisitions, partial buyouts, or recapitalization opportunities.
Employment Type: Full\-time, exempt
Work Arrangement: Remote (possibility to work Hybrid from our Austin office)
Location: US\-based Remote
This role may require approximately domestic travel for client meetings, internal strategy sessions, and product/market events.Role Overview
Lumenci is seeking a GTM \& Customer Success Lead – AI Platform to help launch, commercialize, and scale iLumos.ai a next\-generation AI\-powered patent intelligence platform, across law firms, enterprise corporations, and litigation funders. This highly strategic, customer\-facing role owns the full customer journey for iLumos, from pre\-sales discovery and pilots through onboarding, adoption, renewal, and expansion. This role sits at the intersection of product, go\-to\-market, customer success, consulting services, and enterprise AI adoption, partnering closely with leadership to drive product\-market fit and recurring revenue growth. Over time, this role will help define and build the GTM and customer success function for iLumos, including establishing repeatable processes and, as the business scales, participating in future team hiring and structure.
You will work directly with the Vice President of Product, AI Platform \& IP Intelligence and cross\-functional teams to design and execute pilot programs, lead customer onboarding, drive AI\-enabled workflow adoption, and convert successful usage into scalable commercial engagements.
Key Responsibilities
Pre\-Sales, Pilots, and Commercialization
- Partner with leadership on pre\-sales discovery, customer qualification, and opportunity strategy for prospective iLumos customers.
- Lead tailored product demos, workflow walkthroughs, and value\-based conversations with law firms, corporate IP teams, and litigation funders.
- Structure pilot programs and proof\-of\-concept engagements with clear business objectives, success criteria, stakeholders, and timelines.
- Help scope customer use cases and ensure alignment between customer needs, implementation requirements, and product capabilities.
- Support conversion of pilots and early engagements into subscription, usage\-based, or long\-term commercial relationships.
Customer Onboarding and Adoption
- Serve as the primary customer\-facing lead for iLumos during onboarding and early adoption.
- Guide customers through implementation, enablement, and AI\-powered workflow activation within legal and IP environments.
- Build trusted, long\-term relationships with enterprise stakeholders, executive sponsors, and end users.
- Develop repeatable onboarding and customer engagement processes that support scale across multiple accounts and segments.
Ongoing Customer Success and Expansion
- Drive long\-term adoption, value realization, and retention across customer accounts.
- Identify usage barriers, workflow challenges, and stakeholder risks, and proactively address them through success plans and interventions.
- Partner with customers on adoption strategies and executive reviews tied to measurable business outcomes.
- Identify upsell, expansion, and follow\-on engagement opportunities, and support renewal and expansion revenue.
Go\-to\-Market Strategy and Market Intelligence
- Partner with Lumenci leadership to refine iLumos go\-to\-market strategy across legal, IP, and enterprise segments.
- Help define ideal customer profiles, target accounts, and high\-value early adopter segments.
- Contribute to product positioning, messaging, and commercialization strategy based on customer and market feedback.
- Gather structured market intelligence, customer discovery insights, and competitive observations to inform product roadmap and GTM decisions.
- Collaborate cross\-functionally across product, engineering, consulting, sales, and executive leadership teams.
- Lay the foundations for a scalable GTM and customer success function for iLumos, including playbooks, processes, and, in later phases, input into team structure and hiring.
Who You Are
You are a customer\-centric, commercially minded operator who thrives in fast\-paced, evolving product environments. You are comfortable in pre\-sales discovery conversations, onboarding sessions with end users, strategic reviews with executive sponsors, and cross\-functional discussions with product and consulting teams. You know how to connect pre\-sales strategy, onboarding design, and ongoing customer success into one cohesive experience that drives both customer value and revenue growth.
Required Qualifications
- 6–12\+ years of experience in one or more of the following areas: enterprise SaaS, AI platforms, legal technology, customer success, solutions consulting, product go\-to\-market, consulting, or product commercialization.
- Proven experience in customer\-facing roles that span onboarding, adoption, strategic account management, and/or pre\-sales support.
- Experience supporting enterprise software implementations, pilot programs, proof\-of\-concept engagements, or customer rollouts.
- Demonstrated ability to run discovery conversations, guide product demos, and translate customer needs into solution workflows and business value.
- Strong communication, presentation, and relationship\-building skills with enterprise stakeholders and executive sponsors.
- Experience working cross\-functionally across product, engineering, consulting, sales, and leadership teams.
- Strong analytical thinking, workflow optimization, and problem\-solving capabilities.
Preferred Qualifications
- Experience in one or more of the following: intellectual property, patent analytics, legal technology, litigation consulting, AI products and platforms, workflow automation, B2B SaaS, or enterprise AI adoption.
- Experience in a hybrid customer success \+ pre\-sales / solutions / GTM role.
- Experience helping launch or commercialize a new product, business line, or AI\-enabled workflow.
Key Traits for Success
- Highly customer\-centric and relationship\-oriented.
- Commercially minded and comfortable supporting revenue growth.
- Entrepreneurial, self\-driven, and comfortable with ambiguity.
- Skilled at communicating complex technical concepts in a clear, customer\-friendly way.
- Able to translate AI platform capabilities into measurable customer value and outcomes.
- Effective collaborator across technical, product, consulting, and business teams.
- Comfortable balancing strategic thinking with hands\-on execution.
Why you will love working for Lumenci:
Be Part of a Global Team: Joining Lumenci means joining a diverse and globally distributed team. You'll collaborate with talented individuals from different backgrounds and cultures, bringing unique perspectives to every project.
Growth and Development Opportunities: At Lumenci, we believe in recognizing and rewarding merit. We offer opportunities for merit\-based promotions, allowing you to advance your career based on your performance, contributions, and dedication. We are committed to supporting your professional growth and development, providing the resources and mentorship needed to excel in your role and take on new challenges.
Benefits \& Total Rewards* Comprehensive Health \& Well\-being: We offer robust medical, dental, and vision insurance options that include significant company contributions toward employee premiums to support the health of our "Luminaries" and their families.
- Retirement Strategy: Lumenci provides a 401(k) program with a competitive employer\-matching contribution, enabling employees to build long\-term financial security.
- Performance\-Based Incentives: Our total cash compensation includes a variable pay component designed to reward both individual achievements (KRAs) and overall company success.
- Time Off \& Leaves: We prioritize work\-life harmony through a balanced leave policy that includes accrued Paid Time Off (PTO), designated company holidays, and additional "floating" holidays for personal or cultural significance.
- Holistic Wellness Support: Beyond standard medical care, we provide dedicated Wellness Leave to address both physical health and emotional well\-being, as well as paid leave for significant life events like bereavement and parental bonding.
- Culture of Autonomy \& Growth: Employees benefit from a flexible, remote\-first work environment that favors autonomy and provides structured support for ongoing professional development and career advancement.
Compensation \& Pay Transparency
The expected total annual compensation range for this role is $135,000\-$190,000, which may include base compensation and other eligible incentive components. The final offer will depend on experience, location, and fit within the role's scope.
For candidates in jurisdictions that require pay range disclosures, Lumenci will provide a good‑faith compensation range for the candidate’s location as part of the job posting or during the interview process, consistent with applicable law. In compliance with applicable laws, Lumenci does not request, require, or rely on an applicant’s prior salary history when determining a starting salary or during any part of the hiring process.
Equal Opportunity Employer: Lumenci is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.
Accommodation: If you require a reasonable accommodation to complete this application or participate in the interview process, please let your recruiter know.
Employment Relationship: Nothing in this job description creates or is intended to create a contract of employment for any specific period of time. Employment with Lumenci, if offered, is on an at\-will basis and may be terminated by either the employee or Lumenci at any time, with or without cause and with or without notice, subject to applicable law.
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Salary Context
This $135K-$190K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Lumenci, 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 in Demand for This Role
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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($162K) sits 26% below the category median. Disclosed range: $135K to $190K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Lumenci AI Hiring
Lumenci has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $190K - $190K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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