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About This Role
Company Description About M3: A Japanese global leader in the provision of ground-breaking and innovative technological and research solutions to the healthcare industry. The M3 Group operates in the US, Asia, and Europe with over 5.8 million physician members globally via its physician websites which include mdlinx.com, m3.com, research.m3.com, Doctors.net.uk, medigate.net, and medlive.cn. M3 Inc. is a publicly traded company on the Tokyo Stock Exchange (jp:2413, NIKKEI 225) with subsidiaries in major markets including the US, UK, Japan, South Korea, and China, and in 2020 was ranked in Forbes’ Global 2000 list. The M3 Group provides services to healthcare and the life science industry. In addition to market research, these services include medical education, ethical drug promotion, clinical development, job recruitment, and clinic appointment services. M3 has offices in Japan, UK, France, Germany, Brazil, Sweden, China, USA, and South Korea, as well as India.
Due to our continued growth, we are hiring for an AI Software Engineerto join MDLinx, an M3 company.
About the Business Unit:
MDLinx Mission: Transform Omnichannel from Message Delivery to Belief Engineering
MDLinx is on the path to transform its business and product line-up from endemic to omnichannel engagement model, aiming at fulfilling the promise of true omnichannel approach to pharmaceutical brand promotion – “right message to the right physician at the right time on the right channel”. Our goal is to provide pharmaceutical brands with best-in-class personalized HCP engagement programs across the wider media ecosystem, designed to accelerate disease state and brand knowledge penetration, lead generation, and customer conversion. Our ambition is to leverage an omnichannel approach to establish a new philosophy for physician engagement, shifting from delivery to belief engineering.
Job Description
- Implement features that improve MDLinx and drive impact for its users, with the scope of independent ownership growing over time.
- Contribute to the design of software systems, and participate in the review of other engineers' code.
- Apply software engineering best practices, including automated testing, clean code, peer review, and documentation, to build maintainable and adaptable applications.
- Contribute to the performance, security, and compliance of MDLinx.
- Contribute to the repository context, conventions, automated tests, quality gates, and executable plans that make agentic coding reliable.
- Read AI-generated plans and code critically and raise what looks wrong. Developing this judgment is a primary objective of the first year in the role.
- Find repetitive or time-intensive engineering work that can move to AI-assisted or automated workflows, keeping human review where it protects quality, accuracy, and compliance.
- Troubleshoot bugs in pre-production and production, with support from senior engineers on the team.
- Work with people inside and outside engineering to meet team and company objectives.
- Contribute to projects that benefit M3 USA as a whole, collaborating across business units beyond your own team when the company needs it.
Qualifications
- Associate or bachelor's degree in computer science or a relevant field, or equivalent experience in software engineering.
- Participation in M3's AI training and upskilling. All engineers are expected to attend relevant sessions and engage with these initiatives, and consistent participation is a performance expectation.
- 1 to 3 years of software development experience. Internships, co-ops, academic project work, open-source contributions, and substantial personal projects count toward this.
- TypeScript and React, and Python. Working knowledge is sufficient; depth is expected to develop in the role.
- SQL and relational databases, and version control with Git.
- Familiarity with at least one major cloud platform. MDLinx runs on AWS, GCP, and Vercel, and you will not be expected to know all three coming in.
- Hands-on use of AI coding assistants, with the ability to describe where they helped and where their output needed correction.
- Interest in the media, content production, and pharmaceutical domain, with a commitment to learning it.
- Quick to learn whatever technologies MDLinx uses; with AI assistance, learning speed matters more than prior familiarity with any one stack.
- Clear communication with both technical and non-technical people, and willingness to ask questions early.
Additional Information Benefits:
A career opportunity with M3USA offers competitive wages, and benefits such as:
- Health and Dental
- Life, Accident and Disability Insurance
- Prescription Plan
- Flexible Spending Account
- 401k Plan and Match
- Paid Holidays and Vacation
- Sick Days and Personal Day
- M3 reserves the right to change this job description to meet the business needs of the organization
#LI-MM1
#LI-Remote
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 m3usa, 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. Mid-level AI roles across all categories have a median of $193,200.
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.
m3usa AI Hiring
m3usa has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Fort Washington, PA, US.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
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.
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