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About This Role
About Us
Founded in 2021, Axion is at the forefront of transforming product quality and customer satisfaction in manufacturing. Our cutting-edge AI-powered platform empowers manufacturers to swiftly identify, thoroughly investigate, and effectively resolve quality issues while simultaneously elevating customer experiences and outcomes.
As trailblazers in end-to-end quality intelligence, we're setting new industry standards. Our innovative approach enables industrial, aerospace, consumer, and medtech manufacturers to harness the power of quality and post-market data, driving down costs and boosting business performance.
Our vision extends beyond mere problem-solving; we're committed to reshaping the future of manufacturing. By seamlessly integrating advanced AI technology with deep industry expertise, Axion is paving the way for smarter, safer, and more efficient production processes across diverse sectors.
Backed by leading investors, including Bessemer Venture Partners, Amplo, Boeing, and RTX Ventures, Axion is poised to lead the quality revolution in manufacturing.
About the Role
We’re hiring for a Senior or Staff Software Engineer to help lead our agile, fast-moving backend teams. In this role, you’ll design and build scalable agentic systems, backend services and data-processing workflows that transform complex, unstructured customer data into reliable, structured outputs. . You’ll help shape the architecture of our APIs, databases, cloud infrastructure, and LLM-powered and agentic systems while improving their reliability, observability, and performance. Working closely with engineering, product, and customer-facing teams, you’ll translate ambiguous business needs into clear technical direction and lead foundational decisions that scale with the company. This is a high-impact opportunity to shape the company’s technical strategy and make foundational decisions that will scale with us
Key Responsibilities
- Architect and operate multi-step, tool-using agentic pipelines that convert unstructured data into reliable structured output
- Build evaluation frameworks, golden datasets, and feedback loops that measure quality and catch regressions
- Improve model performance through prompt and pipeline optimization, model selection, and fine-tuning where it pays off
- Own the reliability of cloud-native services: deployment, observability, scalability, and on-call support
- Mentor engineers and lead cross-team technical initiatives from design through production
Requirements
- 5+ years building and operating production backend or data-intensive systems
- Production experience with LLM systems, including multi-step, tool-using, or agentic workflows
- Experience measuring and improving model quality, through evals, prompting, fine-tuning, or a mix
- Experience designing distributed systems, asynchronous workflows, and reliable data-processing services
- Working knowledge of data warehousing, ideally applied to versioned datasets, lineage, or feedback capture
- Experience running containerized applications on a major cloud platform ([AWS/GCP/Azure])
Bonus Points
- Fine-tuning or distillation experience (SFT, LoRA, or provider tuning APIs)
- Experience with LLM observability and cost/latency optimization
Who You Are:
You’re a builder and operator who thrives in fast-moving, high-accountability environments. You take pride in getting things done — thoughtfully, efficiently, and without drama. You’re energized by ambiguity, skilled at bringing clarity, and comfortable flexing between strategy and execution.
You value feedback — giving it, receiving it, and acting on it — and you see collaboration as a competitive advantage, not a burden. You’re low-ego but high-agency: you care about winning as a team more than being right individually. You move quickly, communicate directly, and make decisions grounded in impact and data.
You don’t need constant direction — you create momentum. You take ownership for outcomes, and you expect the same from those around you.
How We Operate:
We move fast, work smart, and hold ourselves to a high bar. Axion is a place for people who take pride in their craft and are motivated by meaningful work. We respect time off and boundaries, but we’re also realistic: hard problems sometimes require weekend pushes or late-night thinking sessions. We support that balance — intensity with respect for recharge.
We stay highly collaborative and connected throughout the day — much of our communication happens over Slack. We move quickly, share feedback often, and keep discussions open so decisions and context flow freely. If you value crisp communication, rapid iteration, and a steady hum of collaboration, you’ll fit right in.
We:
- Collaborate deeply. Feedback is part of how we build — everyone has a voice, and ideas win on merit.
- Leave ego at the door. Titles don’t define value; contribution does.
- Bias toward action. We iterate fast and favor progress over perfection.
- Communicate with clarity. Direct, transparent, and always in service of the mission.
- Act like owners. Everyone is accountable for outcomes, not just tasks.
- Sustain excellence. We push hard but don’t glorify burnout — we’re in this for the long game.
If you want to help shape a company redefining how manufacturing operates — and you thrive in a culture that rewards ownership, speed, and candor — you’ll feel at home here
What We Offer:
- Work with cutting-edge AI technology making a tangible impact in manufacturing
- Collaborative, mission-driven team and supportive leadership
- Generous time off
- Competitive compensation, equity, and benefits
- Lunch stipend…. And much more
Ready to drive the future of manufacturing with AI? Apply today to join our team and help us build the category-defining platform for quality intelligence.
Axion is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.
Compensation Range: $210K - $270K
Salary Context
This $210K-$270K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $192K across 198 roles with salary data).
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 Axion, 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. This role's midpoint ($240K) sits 9% above the category median. Disclosed range: $210K to $270K.
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.
Axion AI Hiring
Axion has 2 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Positions span New York, NY, US, New York, NY. Compensation range: $270K - $270K.
Location Context
AI roles in New York pay a median of $221,000 across 3,078 tracked positions. That's 4% above the national 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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