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About This Role
About Us: EvolutionIQ builds AI that helps insurance claims teams handle claims more accurately, fairly, and efficiently, so more people impacted by injury or illness can get back to their lives with dignity and stability. As part of CCC Intelligent Solutions (NASDAQ: CCC), we pair AI\-native product development with something almost no one else in this market has: 40 years of proprietary data and deep relationships with the largest, most complex carriers in the world. It's a rare combination, and it's what lets us build casualty products others can't.
Our people come first, and we think it shows. We've been named one of Inc.'s Best Workplaces three years running, plus Built In's Best Places to Work in 2025 and 2026\.
The Mission: EvolutionIQ is seeking to scale our infrastructure, systems, and people to support an agentic future for the insurance industry. We are looking for a Senior Staff or Principal Software Engineer who is a pragmatic visionary who will serve as a high\-leverage force multiplier across the entire organization.
In this role, you will drive the technical vision for our new agentic products and the growth of our platform. You will solve our most complex technical bottlenecks and serve as the critical bridge between executive strategy and engineering execution. Your mission is to ensure our technical roadmap directly supports our product goals while leveling up the software engineering rigor across our 100\+ person organization.
What You'll Achieve:
- Architect the Agentic Future: Lead the transition from traditional data pipelines to event\-driven, agentic systems that handle tens of millions of unstructured documents with world\-class stability.
- Bridge the Platform\-Product Divide: Act as a critical interface to ensure the Platform team builds generalized, high\-utility tools that solve real problems for Product Engineers.
- Accelerate the SDLC: Use first principles thinking to leverage AI and agentic tools to accelerate the entire software development lifecycle—from testing to deployment—ensuring we maintain high throughput as we scale.
- Drive Organizational Influence: Partner with the CTO and EVP of Product and Technology to align technical strategy with business outcomes. You will influence the adoption of modern technologies by building the right environment for teams to succeed.
- Pragmatic Implementation: Rapidly turn ideas into thoughtful designs with multiple options and trade\-offs. You will lead the "1 to 10" journey towards iterative, startup\-ready progress.
About You:
- The Pragmatic Architect: You have a startup\-first mindset. You know when to build for 10x scale and when over\-engineering will hinder the company. You value getting stuff done and iterative bridging over theoretical rewrites.
- Product\-Minded Engineer: You can translate high\-level business needs into technical requirements. You think like a PM, are comfortable writing a PRD, and can effectively push back against stakeholders to ensure technical work delivers actual business value.
- Battle\-Tested Leader: You have seen the "1 to 10" scale\-up journey. You possess the startup rigor to move fast, combined with the enterprise wisdom to build systems that don't break under massive volume.
- Technically Polyglot: You have a deep software engineering foundation but understand the emerging agentic landscape (embeddings, RAG, retrieval) at a level that commands respect from Staff\-level SMEs.
- Expert Communicator: You are an over\-communicator by nature. You break down silos and can explain complex technical trade\-offs to both junior engineers and executive leadership.
Work\-life, Culture \& Perks
- Compensation: The base salary range is $275\-330K (based on level hired), with flexibility depending on a candidate's background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our generous compensation package (total comp between $380\-450K depending on level).
- Well\-Being: Medical, dental, vision, short \& long\-term disability, life insurance and AD\&D, and 401k matching. Additional family, wellness, and pet benefits.
- Home \& Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work.
- Office Life: Catered lunches, happy hours, pet\-friendly spaces, and monthly technology stipend.
- Growth \& Training: $1,000/year for each employee for professional development, as well as opportunities for tuition reimbursement.
- Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa.
*EvolutionIQ appreciates your interest in our company as a place of employment. EvolutionIQ is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.*
Salary Context
This $275K-$330K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At EvolutionIQ, 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 $218,500 based on 729 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($302K) sits 38% above the category median. Disclosed range: $275K to $330K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
EvolutionIQ AI Hiring
EvolutionIQ has 4 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Based in New York, NY, US. Compensation range: $225K - $330K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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