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About This Role
Convoso is a leading AI-powered contact center platform purpose-built for revenue teams. Since 2006, Convoso has remained at the forefront of innovation, consistently developing solutions to drive customer growth while supporting adherence to regulatory standards.
Who We Are:
While headquartered in Los Angeles, the Convoso team can be found around the globe working in either a hybrid or remote capacity. Awarded as a "best place to work" company, our culture fosters team integrity, positive persistence, and continuous growth.
Our core platform powers successful sales teams across multiple industries, giving our customers a competitive edge and streamlined productivity. With built-in Al and automations, our product is a premium offering in a competitive space. We continue to grow our product capabilities to better serve our current customers and to expand into newer markets.
Convoso is looking for people who are excited about technology and innovation. We are a company of motivated team players with diverse backgrounds driving accelerated growth in a supportive, positive culture.
Most roles at Convoso function as "hybrid" with some opportunities for travel to in-person business events and company meetings. For remote positions, Convoso's U.S. hiring is open to candidates residing anywhere within the United States.
The Job:
We are looking for an experienced Principal Software Engineer to build and scale the AI agent systems within our enterprise SaaS application. In this role, you will be responsible for the core engineering of agentic logic, frameworks, and the high-performance backend infrastructure required to support intelligent automation at scale.
Responsibilities summary:
- Build AI Agent Frameworks: Develop the internal agents, LLMs, logic and reasoning loops, that allow AI agents to perform complex, multi-step tasks.
- Develop Core SaaS Features: Engineer robust, full-stack enterprise web components, ensuring high performance and security across the application.
- Data Engineering: Manage and optimize the interface between our AI agents and data.
- Engineering Excellence: Write clean, secure, and maintainable code and lead rigorous code reviews and refactoring initiatives.
- Automated Testing: Design and implement unit and functional tests to ensure the reliability of both traditional code and non-deterministic AI workflows.
Who You Are:
- AI Agent Architecture: Expert-level ability to build and orchestrate autonomous agents capable of planning, reasoning, and executing multi-step tasks via reasoning loops (e.g., React).
- Orchestration: Direct experience developing the internal logic and interface layers that allow LLMs to interact with APIs, databases, and system functions.
- AI Reliability & Testing: Hands-on ability to create automated unit and functional testing suites specifically designed to validate non-deterministic AI agent outputs and workflows.
- LLM Implementation: Extensive experience developing production-grade features using LLM APIs (OpenAI, Claude, etc.), including context window management, prompt optimization, and cost-monitoring.
- AI-Assisted Development: Expert proficiency in using tools like GitHub Copilot or Claude to accelerate engineering velocity and maintain high code quality.
- Data Layer for AI: Proficiency in MySQL and relational databases, with the ability to write complex, raw queries to feed high-scale enterprise data into agentic workflows.
- Production Go at scale: Strong grasp of Go concurrency patterns, memory management, garbage collection behavior, and profiling.
- Network & Systems Fundamentals: Deep comfort with Linux/POSIX systems, networking primitives (TCP/UDP sockets, WebSockets, gRPC)
- High-reliability & Data Integrity: Proven experience designing transactional state machines, resilient webhook/event pipelines, and defensive API integrations.
- Production Ownership: Engineers who write integration tests, stress tests, instrument their own observability and debug end-to-end.
Enterprise SaaS Foundations: 10+ years of experience in software engineering, design patterns, and clean coding practices to large-scale web applications.
- Model Lifecycle: Practical knowledge of model evaluation, experiment tracking, and performance monitoring in a production environment.
- Business Prioritization: Strong problem-solving skills focused on translating complex business needs into prioritized technical development.
Nice-to-Haves (domain experience):
- Real-time audio, WebRTC, VoIP (SIP/RTP), or media streaming
Work Perks Worth The Hype:
- Competitive compensation package
- Stock options
- 100% covered premiums for employees; Medical, Dental, Basic life insurance, Long term disability
- Affordable Vision plan and optional FSA
- PTO, Paid Sick Time, Holidays, Bereavement time, Parental Leave
- Your birthday off
- 401k program with generous company match
- No cost Employee Assistance Program and Travel Assistance
- Monthly Gym membership reimbursement
- Monthly credits toward food & beverage
- Company Outings
- On and offsite team building events
- Paid training for departments
- Apple laptop (most roles)
- And a team of highly experienced and kind colleagues!
- HQ Office:
- Casual office environment & dress
- Daily catered lunches
- Fully stocked kitchen (Dietary restriction-friendly)
- Happy Hours
- On-site Car Wash
- Free Parking
Compensation:
The base salary range is: $200,000 - $230,000
The Base Pay Range for this position is based on the industry benchmark for position, function, level and the company's compensation strategies. However, final offers may vary from the amount listed based on geography, candidate experience and expertise, and other objective business. Convoso's compensation package also includes equity for all eligible U.S full time roles and exceptional benefits, including generous 401k match.
Your California Privacy Rights:
As a California resident who is an applicant to be an employee of Convoso, you have certain rights under California law with respect to information collected by Convoso in the course and scope of its evaluation of your application. The types of information Convoso collects and your rights with respect to that information are contained in Convoso's privacy policy, which you can review by going to https://www.convoso.com/privacy-policy/.
Salary Context
This $200K-$230K range is above the median 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 Convoso, 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. Disclosed range: $200K to $230K.
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.
Convoso AI Hiring
Convoso has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Los Angeles, CA, US. Compensation range: $230K - $230K.
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.
Frequently Asked Questions
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