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About This Role
At Postali, our work is rooted in a simple belief: when our clients succeed, we succeed. Since 2009, we've helped law firms across the country grow through thoughtful, strategic marketing tailored to real business goals. We're proud to have been recognized as one of Columbus Business First's Best Places to Work, a reflection of the collaborative, growth\-oriented culture we've built and the long\-term relationships we've fostered with both our clients and team members.
Search is changing faster than it has in two decades. Google's AI Overviews and AI Mode, along with ChatGPT and Claude, are reshaping how people find and choose a lawyer. Most agencies are still trying to figure out what that means. We are actively building for it.
Our team is investing heavily in AI, automation, and new ways of delivering results for our clients. We believe the future belongs to organizations that combine human expertise with intelligent systems, and we're looking for someone who wants to help build that future. If you're excited by experimentation, systems thinking, and the opportunity to shape how SEO works in an AI\-first world, you're the right candidate.
About the Role
This is a position based in Columbus, Ohio. We believe collaboration is strongest when our team works together in person, but we are open to a hybrid arrangement for the right senior candidate.
The SEO \& AI Search Director owns search performance for our law firm clients across three tracks (organic, Google Maps and local, and AI\-answer visibility), and leads the design and day\-to\-day operation of the agentic AI workflows that power all three. It is a hands\-on, build\-it role that blends three skill sets: a modern SEO and GEO strategist, an AI\-workflow engineer, and a team leader.
You will work alongside an AI agent system that can diagnose a client, analyze competitors, draft on\-site and content fixes, and assemble citation and reporting work. Your job is to engineer those workflows, supply the expert judgment and approvals the agent cannot, and turn the output into rankings and leads. You will also lead and mentor our SEO team and partner closely with content, design, development, and account management.
What You'll Do
- Own performance across three tracks, each with its own workflow and measurement: Organic (Ahrefs and Google Search Console), Google Maps and Local (Google Business Profile, citations and NAP consistency, reviews, BrightLocal), and AEO/GEO (being the cited answer in AI Overviews, ChatGPT, and Claude, measured by AI share of voice and citation share).
- Continuously improve our agentic SEO workflows: the step\-by\-step "skills" the AI follows, its connections to our tools (Ahrefs, BrightLocal, Search Console, WordPress, Wrike, Notion), the prompts and quality checks, and the automations and scheduled tasks. You decide how the work should be done, then make the system do it reliably.
- Be the human in the loop. Review and approve the agent’s recommendations, content, and on\-site changes before anything goes live; authorize link and citation spend against client budgets; sign off on attorney\-advertising and E\-E\-A\-T compliance; and promote changes from staging to production.
- Run the diagnosis, action, and measurement loop for each client: find why rankings and leads have softened, pinpoint the recoverable money keywords, fix on\-site and content, and prove the recovery.
- Lead deep competitor analysis in Ahrefs (content gaps, backlink and link\-intersect gaps, domain\-rating trajectory) and turn it into a prioritized plan.
- Own the link and citation program on a register\-to\-achieve model (legal directories, bar and chamber and association memberships, sponsorships, awards, and citations), managed within budget, with renewals, credentials, and NAP consistency tracked in our system of record.
- Audit and correct the tracking setup. Reconcile the keywords and configurations across Wrike, BrightLocal, Ahrefs, and our documentation, and fix outdated or incorrect targets rather than trusting what is already there.
- Define and report the metrics that matter, including new ones for AI visibility where traditional metrics fall short, and tie ranking movement back to client leads. Build clear, refreshable client dashboards.
- Lead and mentor the SEO team, set standards and SOPs, and collaborate across content, design, development, and account management.
- Stay ahead of AI search. Test new tactics and tools and adapt the playbook as Google and the AI engines evolve.
Why This Role Is Different
Most SEO leadership roles are about directing people. This one is about directing people and an AI system. We have already architected an agentic platform that runs the SEO and GEO loop across all three tracks. You will be the expert who owns it, improves it, and provides the human judgment, approvals, and domain expertise it depends on. If the future of search excites you, and you want to build the operating system that wins it rather than just react to it, this is a rare seat.
What We're Looking For
- 5\-7\+ years in SEO with a track record of results, including hands\-on organic, local and maps, and emerging AEO/GEO work. (Titles and exact years are flexible for the right person. If you've spent your career creating systems, solving problems, experimenting with AI, and figuring things out \- even if you've never held a Director title before\- we encourage you to apply).
- Deep, current command of the modern stack: Ahrefs (or equivalent), Google Search Console, Google Business Profile, a local SEO tool such as BrightLocal, and WordPress with Yoast.
- Real technical and automation ability. You are comfortable working with AI agents and large language models, connecting tools and APIs, writing and refining prompts or reusable "skills," and building automations. You do not need to be a software engineer, but you should be the kind of person who reads the documentation, builds the workflow, and improves it. (Experience with tools such as n8n, Make, or Zapier, with API connectors, or with Claude\- or ChatGPT\-based agents is a strong plus.)
- Strong technical SEO and structured data (Schema.org and JSON\-LD) for both classic search and AI comprehension.
- A measurement mindset, including comfort defining new KPIs where standard metrics do not yet capture AI visibility, and the ability to make data tell a clear story to clients and the team.
- Sound judgment in a regulated space. You understand, or will quickly learn, attorney\-advertising rules, E\-E\-A\-T, and YMYL (your\-money\-or\-your\-life) standards, and you are comfortable being the approver who keeps the work compliant and on brand.
- Leadership and communication. You can lead and mentor a team, set process, and explain complex AI and search concepts clearly to clients and colleagues.
- A builder's mindset. You are comfortable with ambiguity, you write the manual rather than wait for one, and you enjoy turning a new idea into a repeatable system.
Great to Have
- Experience in legal marketing or another regulated or service\-based industry.
- Familiarity with Wrike or a similar project management tool, and with reputation and review management.
- Comfort reading an API doc or writing light scripts (for example, simple Python). Not required.
- Strong Excel or Google Sheets skills.
The Tools You'll Work With
Ahrefs, BrightLocal, Google Search Console, Google Business Profile, WordPress and Yoast, Wrike, and Notion, plus our in\-house agentic AI platform built on Claude (with connectors to the tools above). You will partner closely with our Director of Marketing Technology \& AI to design, improve, and operationalize the AI workflows that power our SEO, local, and AI search initiatives.
Job Details
- Full\-time
- Office is in Columbus, Ohio. Open to hybrid for the right candidate.
- Compensation: $110,000\-$130,000 depending on experience in SEO, local search, AI search visibility, workflow automation, agentic development, and team leadership.
- Benefits: 401(k); health, dental, and vision insurance; life insurance; paid time off; and parental leave.
How to Apply
You do not need to check every single box. If you are an excellent SEO who is genuinely excited to help engineer and lead an AI\-native practice, we want to hear from you.
Apply through Indeed, or contact Kate Collins, Managing Director, [email protected]
Pay: $110,000\.00 \- $130,000\.00 per year
Benefits:
- 401(k)
- Dental insurance
- Health insurance
- Paid time off
- Parental leave
- Vision insurance
Experience:
- SEO: 5 years (Required)
Location:
- Columbus, OH 43215 (Required)
Work Location: In person
Salary Context
This $110K-$130K 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 Postali LLC, 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. Director-level AI roles across all categories have a median of $247,800. This role's midpoint ($120K) sits 34% below the category median. Disclosed range: $110K to $130K.
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.
Postali LLC AI Hiring
Postali LLC has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Columbus, OH, US. Compensation range: $130K - $130K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
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.
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