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About This Role
Do you want to empower organizations to build smarter compensation strategies while ensuring fair pay for all employees?
Syndio is the leading pay governance and compensation intelligence platform. We help organizations make better pay decisions at every stage of the compensation lifecycle, from leveling and offers to promotions and merit. Our platform gives HR, compensation, and finance leaders the data and decision support they need to govern pay fairly, compliantly, and with confidence. We partner with many of the world's most recognized and respected enterprises, helping them implement leading\-edge compensation solutions with expert guidance and analyzing pay for over 10 million employees across the world.
Join us in our mission to help companies make smarter pay decisions they can trust!
About the Role:
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Syndi is Syndio's AI platform — one shared agent experience (in\-product chat, Slack, Teams) serving our product lines, built on syndi\-api: an agent runtime owning orchestration, tool calling, memory, RAG, evals, and observability, live in production today. The platform is young (v1 shipped this quarter), moving fast, and designed around a clear operating model: product teams contribute domain content through APIs, evals, and knowledge — the platform owns the experience.
We're hiring a staff\-level engineer to take ownership of major runtime surfaces and grow into a technical owner of the platform. This is a high\-autonomy role on a small team (3–4 engineers): you'll design, ship, and operate systems end\-to\-end, and you'll work directly with product\-team owners through the platform's contribution seams.
What You'll Work On
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- Core runtime surfaces of syndi\-api: the agent loop, tool execution and registry, memory, context management (Python, Postgres, Claude on Vertex, GCP).
- The eval system — offline gates and online detector/judge evals written onto production traces — and its growth as product teams adopt it.
- Production operation: observability (Datadog LLM Obs), incident response, the reliability of an agent surface real customers use.
- The platform's contribution seams: reviewing product teams' tool wrappers and evals, evolving the GET /tools registry and drift\-detection contract.
- Clarifying, designing, and implementing compliance and legal requirements for Syndi.
What We're Looking For
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- 5\+ years building production backend systems; deep comfort with Python, relational stores, and cloud infra (we're on GCP/Kubernetes).
- You've built LLM\-powered systems in production — an agent loop, tool\-calling integration, RAG, or eval infrastructure — and have opinions from the scar tissue.
- You design for operability: legal compliance, tracing, evals, and kill switches are part of the feature, not afterthoughts.
- You can own a technical domain with light supervision: propose direction in writing with clear API specs, take review, ship, and carry the pager for what you shipped.
- Strong written communication — our operating model runs on design docs and PR review across team boundaries.
- Nice to have: experience being the platform side of a platform/product relationship; SSE/streaming systems; compliance\-adjacent engineering (data minimization, auditability); prior Staff scope.
Why you'll love it here:
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- Competitive Compensation. For this role our salary is targeted at $205\-225k USD or $180\-200k CAD per year. Final offer amounts are determined by factors such as experience and expertise.
- Syndio Equity. So you can share in Syndio's success
- Flexible Vacation Policy. We encourage our team to recharge when they need to (up to 20 days PTO in Canada) plus paid sick \& safe time, compassion leave, and voting leave.
- Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents.
- Life Insurance \& Disability. Syndio covers the full premium.
- Remote\-first in US \+ Alberta; in Calgary, non\-mandatory office available \#LI\-Remote
Role Progession
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- First 30 days: Focus on onboarding, mastering our core agent runtime surfaces, and shipping a small\-scale contribution to understand the platform's contribution seams.
- First 60 days: Independently manage core runtime surfaces, troubleshoot complex issues, and start co\-owning a consumer team's integration from API design to eval sign\-off.
- First 90 days: Concretely ship a major runtime capability end\-to\-end (e.g., multimodal input or a new channel surface), take on\-call for the platform, and co\-own a consumer team's integration from API design to eval sign\-off.
The interview overview
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Below you'll find an outline of the interview plan for our Senior Software Engineer (AI Platform) position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.
- Recruiter Screen (25 min)
- Hiring Manager Interview (30 min)
- Technical Evaluation \- Design Skills (60 min)
- Crossfunctional Team Interviews (2 x 30 min)
At Syndio, we're building a diverse team that values candor, curiosity, and community. If you share these values and are interested in joining us, we'd love to talk with you even if you don't 100% meet the "about you" listed here. We don't expect anyone to have all the answers, as long as you're willing to learn and grow with us.
Syndio is an Equal Opportunity Employer. We are building an inclusive and collaborative workplace as we grow, and we welcome team members regardless of gender/identity, sexual orientation, race or cultural background, religion, physical disability and age.
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 Syndio, 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.
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.
Syndio AI Hiring
Syndio has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Portland, OR, US.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% 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 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.
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