Interested in this AI Software Engineer role at Think Big Solutions?
Apply Now →Skills & Technologies
About This Role
About AroundHI
AroundHI works with world\-class clients across multiple industries to identify and place skilled professionals. We support our partners by recruiting experienced talent who can contribute immediately and grow within project\-driven environments.
Location: San Francisco, CA (Onsite 5 Days/Week)
Job Type: Full\-Time
About the Role
We are looking for a Software Engineer to build and deploy AI\-powered applications and automation solutions for large enterprise environments.
In this role, you will work on production systems that integrate with platforms such as Salesforce, NetSuite, Microsoft Dynamics 365, and other enterprise applications. You'll collaborate closely with technical teams to deliver scalable solutions that automate complex business processes and improve operational efficiency.
This position is ideal for engineers who enjoy solving challenging problems, taking ownership, and shipping high\-quality software in fast\-paced environments.
Responsibilities
- Design, build, and deploy AI\-powered applications and automation solutions
- Integrate with enterprise systems including CRM, ERP, and business platforms
- Develop scalable backend services and APIs
- Build production\-ready software with a focus on reliability and maintainability
- Troubleshoot and optimize existing systems and workflows
- Collaborate with engineering and business stakeholders to deliver solutions
- Contribute to architectural decisions and technical direction
- Take ownership of projects from design through deployment
Required Qualifications
- 1–4 years of professional software engineering experience
- Strong software engineering fundamentals and computer science knowledge
- Experience building and deploying production software
- Experience working with APIs, integrations, or distributed systems
- Hands\-on experience with AI technologies, including LLMs, agent frameworks, AI APIs, or automation workflows
- Strong problem\-solving and systems\-thinking skills
- Ability to work independently in ambiguous environments
- Comfortable receiving feedback and iterating quickly
- Willingness to work onsite in San Francisco
Preferred Qualifications
- Experience building AI applications, agents, or workflow automation solutions
- Startup or high\-growth company experience
- Experience integrating with enterprise systems such as Salesforce, NetSuite, or Microsoft Dynamics 365
- Experience with agent frameworks, orchestration tools, or AI infrastructure
- Active GitHub, open\-source, or personal technical projects
- Experience leading projects or mentoring junior developers
Ideal Background
We're particularly interested in engineers who enjoy building products from the ground up, move quickly without sacrificing quality, and have demonstrated the ability to take ownership of technical challenges.
Candidates who can clearly explain systems they've built, technical decisions they've made, and lessons learned from production environments will stand out.
What Success Looks Like
- Delivering production\-ready software quickly and reliably
- Taking ownership of technical challenges without waiting for detailed direction
- Building scalable solutions that integrate with enterprise systems
- Growing into increased technical leadership responsibilities over time
Pay: $175,000\.00 \- $225,000\.00 per year
Work Location: In person
Salary Context
This $175K-$225K range is above the median for AI Software Engineer roles in our dataset (median: $190K across 219 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 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Think Big Solutions, 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 $232,000 based on 797 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($200K) sits 14% below the category median. Disclosed range: $175K to $225K.
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.
Think Big Solutions AI Hiring
Think Big Solutions has 1 open AI role right now. They're hiring across AI Software Engineer. Based in San Francisco, CA, US. Compensation range: $225K - $225K.
Location Context
AI roles in San Francisco pay a median of $253,000 across 2,168 tracked positions. That's 26% 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 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).
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 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.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.