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About This Role
Meet the Moment with Alteryx
We're living through a once\-in\-a\-generation shift in how work gets done. Data, automation, and AI are quickly becoming the center of every business decision \- and Alteryx is leading the transformation.
You'll be working on the challenges that sit at the heart of modern business. No matter your role, the work you do will help organizations move faster, see more clearly, and tackle questions that used to feel impossible.
If you're ready to meet the moment with innovation, curiosity, and excellence, there's a place for you here.
Alteryx is searching for a Sr. Software Engineer (Back\-End) . This position is remote\-friendly.
Position Overview:
We’re looking for a Senior Software Engineer to help build and scale the backend systems that power AI experiences across Alteryx. This is primarily a Python backend role focused on the services, APIs, orchestration layers, and platform integrations behind Copilot / Ask Alteryx and related AI capabilities. In addition to core backend engineering, this role also flexes into agent systems work when needed, contributing to the service\-side AI workflows, MCP\-connected skills, and orchestration patterns that make those experiences useful.
You’ll work across core backend services and adjacent agent systems that connect Alteryx products and domain capabilities into a shared AI platform. That includes APIs and service integrations, authentication and authorization flows, telemetry and observability, data and tool orchestration, and the infrastructure needed to run reliable, scalable AI systems in production.
This is intentionally a flex role. Depending on roadmap priorities and delivery pressure, you may spend more time in a given quarter on core backend service work or more time on agent systems and AI orchestration. In practice, we expect this engineer to move fluidly between backend and agent responsibilities based on where the team most needs senior capacity, but the center of gravity is backend engineering.
This role is a strong fit for an engineer who can independently deliver medium\-sized projects end\-to\-end, contribute to technical design, and move comfortably between application backend work and agent\-oriented problem solving. You’ll help turn ambiguous product opportunities into reliable customer\-facing capabilities while balancing speed, craft, maintainability, and operational rigor.
Primary Responsibilities:
- Owning and delivering backend features in the Python services that power Copilot / Ask Alteryx and adjacent AI experiences.
- Designing and implementing APIs, service integrations, and orchestration logic that connect UI surfaces, backend systems, and AI capabilities.
- Flexing into agent workflows, tool execution paths, and MCP\-oriented integrations when roadmap needs require backend engineers to support agent delivery.
- Partnering with product, design, frontend, data science, and platform teams to explore problem spaces, clarify requirements, and ship customer\-facing improvements.
- Improving service reliability through thoughtful work on observability, testing, performance, rate limiting, background processes, and operational readiness.
- Contributing to software design, code reviews, technical planning, and engineering practices that improve quality and delivery velocity.
- Mentoring engineers through thoughtful feedback, pairing, and day\-to\-day technical collaboration.
- Helping the team respond quickly to new AI opportunities while making sound tradeoffs around correctness, cost, security, and maintainability.
Requirements:
- 4\+ years building production backend systems in Python, including experience with APIs, service integrations, and maintainable application design.
- Experience building or maintaining backend services with frameworks such as FastAPI, Flask, Django, or similar.
- Solid understanding of distributed systems fundamentals, including service\-to\-service communication, authentication / authorization, observability, and failure handling.
- Experience with relational databases, caching, and stateful service dependencies such as PostgreSQL, Redis, or similar technologies.
- Demonstrated ability to own features or medium\-sized projects end\-to\-end, from design and implementation through testing, rollout, and iteration.
- Strong experience with automated testing across unit, integration, and end\-to\-end layers.
- Working knowledge of CI/CD practices and modern development workflows using tools such as GitLab or GitHub.
- Ability to collaborate effectively with product, design, data science, and engineering partners in ambiguous problem spaces.
- Comfort working across both conventional backend engineering and agent\-oriented development, with the judgment to shift focus based on delivery needs.
Valued Skills:
- Experience building AI\-assisted, LLM\-powered, or agentic product experiences.
- Experience with agent orchestration frameworks such as LangGraph, LangChain, or similar patterns for tool\-using AI systems.
- Experience with MCP, extensibility platforms, or tool\-based integration models.
- Experience with retrieval, grounding, evaluation, or other patterns used to improve AI system quality and reliability.
- Experience with Google Cloud, Vertex AI, Kubernetes, Kafka, or similar cloud\-native and platform technologies.
- Familiarity with frontend or product integration work that helps connect backend AI capabilities to real user experiences.
About You:
You’re passionate about building great software and want to have a direct impact on how AI capabilities are delivered across Alteryx products. You work independently, communicate clearly, and know how to make progress in ambiguous spaces without over\-engineering the solution. You’re comfortable working on both conventional backend engineering problems and newer agent\-oriented systems, and you care about reliability, customer value, and helping the team get better through collaboration, mentorship, and a strong engineering mindset.
Compensation:
Alteryx is committed to fair, equitable, and transparent compensation. Final compensation is determined by several factors, including but not limited to relevant work experience, education, certifications, skills, and geographic location.
The salary range for this role in the United States is $118,700 \- $153,900\.
Bonus payouts are based on individual and company performance.
In addition to base pay and bonus eligibility, this role includes clear forms of additional compensation, such as:
- A monthly Connectivity Plus stipend of $150 to support remote work\-related expenses
- An annual $200 home office reimbursement
Alteryx offers a comprehensive benefits package designed to support your health, financial security, and overall well\-being, including:
- Medical, dental, and vision coverage
- 401(k) with company match
- Paid parental leave, caregiver leave, and flexible time off
- Mental health support and wellness reimbursement
- Career development and education assistance
*Interested? Learn more and apply today at alteryx.com/careers!*
\#LI\-EM1
\#LI\-REMOTE
Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences .
Benefits \& Perks:
Alteryx has amazing benefits for all Associates which can be viewed here .
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Alteryx will consider for employment qualified applicants with arrest and conviction records.
This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.
Salary Context
This $118K-$153K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $189K across 518 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 26,159 AI roles we're tracking, AI Software Engineer positions make up 2% of the market. At Alteryx, 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 $235,100 based on 665 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($136K) sits 42% below the category median. Disclosed range: $118K to $153K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Alteryx AI Hiring
Alteryx has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, Data Scientist. Positions span CA, US, Remote, US. Compensation range: $153K - $240K.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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