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About This Role
We are PMG
PMG, a global independent platform company engineered for impact, integrates business strategy, media, creative, and data within a single operating model powered by our proprietary operating system, Alli. With more than 1,000 employees, PMG partners with brands including Apple, Nike, Dropbox, Experian, Sephora, and Whole Foods. Our work has earned top industry honors, including Cannes Lions and Adweek's Media Plan of the Year, and PMG has won 40+ workplace culture awards, including being the only company to rank among Ad Age's Best Places to Work for 11 consecutive years.
Who You Will Be Working With
As the AI & Software Engineering Senior Manager, you'll work within Alli, our proprietary digital marketing platform. This group is dedicated to building organizational tools that help orchestrate multimillion-dollar budgets and enable seamless collaboration across globally integrated teams, supporting some of the world's most recognizable brands.
In this role, you'll work alongside engineers, product managers, and designers who thrive on tackling challenging problems and building innovative solutions. Together, you'll leverage AI-powered tools and cutting-edge technology to transform how digital marketing strategies are developed and executed. This team doesn't just dream up ideas—we bring them to life, delivering real-world impact for our clients and the industry at large.
Our collaborative and fast-paced environment fosters creativity, growth, and innovation. You'll play a critical role in defining the technical vision and roadmap, driving solutions to complex challenges like data unification, AI-driven automation, and scalable system design. This is an opportunity to lead with purpose, inspire your team, and contribute to a product that's shaping the future of digital marketing.
What You'll Be Doing
- Define and manage a multi-year product roadmap in collaboration with Product Managers and Designers to create transformative products.
- Drive innovative projects with a high impact on the media and advertising industry.
- Build and oversee the implementation of complex data integrations via APIs and other common methods.
- Design and manage highly scalable technical solutions, ensuring architectural excellence and cutting-edge performance.
- Conduct code reviews, mentor junior engineers, and provide constructive feedback to help grow your team's technical expertise.
- Collaborate closely with cross-functional Data & Tech teams to integrate solutions across Alli.
- Champion agile methodologies, maintaining high team productivity and fostering a collaborative, inclusive culture.
- Work within a dynamic environment that embraces short decision-making processes and empowers innovation.
What You Will Bring
- 6+ years of hands-on experience as a software engineer working across the entire SDLC.
- 3+ years leading and managing a team of 5–10 highly skilled developers in an agile SCRUM environment.
- 2+ years working with the MERN stack (MongoDB, Express.js, React, Node.js) or a similar skill set with Python or Go.
- 3+ years of experience working within AWS cloud environments using ECS, Fargate, Lambdas, SQS, Postgres and other similar technologies
- Familiarity with infrastructure-as-code tools such as Terraform, Ansible, Chef, or Puppet to streamline deployments.
- Experience or interest in Generative AI, Large Language Models (LLMs), and platforms like OpenAI, Gemini, Bedrock, or LangChain.
- Experience building a team from the ground up
- Proficiency in automated testing, code reviews, clean code principles, and refactoring strategies to ensure high-quality code.
- Hands-on experience building and scaling RESTful APIs for robust and efficient systems.
- Proficiency in Docker or Kubernetes, with experience managing configurations in containerized environments.
- A commitment to curiosity and adaptability as a continual learner, staying at the forefront of media innovation while prioritizing client success with a customer-focused mindset that seeks opportunities to deliver meaningful value.
What We Offer
- Professional Development: Take advantage of our learning and development programs, mentorship opportunities, and career advancement support.
- Generous Time Off: Enjoy generous paid time off and holiday allowances to recharge and spend time with loved ones.
- Parental Leave: We provide paid parental leave to support your family during important life events.
- Retirement & Pension Plans: Plan for your future with competitive retirement or pension programs, including contribution matching.
- Fertility and Family Support: Access fertility benefits for all team members and their spouses.
- Healthcare: Coverage and support for everyday medical expenses and routine care, tailored by geography.
- Pet Insurance: Protect your pet's health and your finances.
- Lifestyle Spending Accounts: Enjoy 100% company-funded accounts to promote healthy habits and well-being.
- Commuter Benefits: Access support for travel and commuting needs, where available.
- Annual Bonus: All employees are eligible for an annual bonus.
- Volunteering Opportunities: Receive 8 give-back hours to volunteer in your local communities.
- AI Enterprise License: Access AI Enterprise accounts and participate in weekly AI training sessions to empower and ensure AI safety.
Benefits vary by country, location, and geography to reflect local laws, norms, and expectations.
What Sets Us Apart
Being part of PMG means joining a company culture that's unmatched in digital. We're dedicated to working hard to serve our employees and clients, delivering value, results, and innovation—which often requires true grit and agility. We believe in taking care of ourselves and each other to continuously improve in every way.
In alignment with our core values to be inclusive and always change for the better, PMG is committed to creating a more diverse and inclusive culture, and we are proud to be an equal opportunity employer. We believe that we only change for the better by bringing diverse perspectives to our company. PMG recruits, employs, trains, compensates, and promotes regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At PMG Digital Company, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
PMG Digital Company AI Hiring
PMG Digital Company has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Dallas, TX, US.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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