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About This Role
From Fivetran's founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We're proud that more organizations continue to leverage our technology every day to become truly data\-driven.
About Us
Fivetran and dbt Labs are bringing together two industry\-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we're delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we're building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It's an exciting time to join us: we're creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.
About the Role
Fivetran and dbt are building the open data infrastructure that powers AI agents you can trust.
Fivetran is looking for a Senior Staff R\&D Software Engineer to join our fast\-growing Fivetran AI team. Your data stack was built for humans — but agents are the new primary data consumers, and they have fundamentally different requirements. Agents can't intuit context; it must be explicitly codified, governed, and traceable. We're building the governed context layer that solves this problem: Agents Schema, an open standard for storing agent\-ready context directly in the customer's own data warehouse, and Context Builder, the managed service that keeps it filled and fresh.
This role goes well beyond standard engineering. You'll research emerging techniques in the fast\-moving AI landscape and bring real product and market understanding to decide which ideas are worth pursuing — and then you'll take what you've learned and ship it as production software. We're looking for a true generalist who is willing and able to wear whatever hat the moment calls for: prototyping a new retrieval technique one week, hardening a backend service the next, then doing SRE or QA work when the team needs it. At this level, you're a trusted expert beyond your own department — your judgment shapes technical direction across Fivetran AI and the teams it depends on, you define your own direction rather than waiting for it, and you execute with the highest level of independence. Fivetran AI operates like a startup within Fivetran, and we need engineers who thrive on that range and ambiguity rather than staying in one lane.
Fivetran is the epitome of data\-driven development — our engineering team is focused on building a world class product that:
- Builds Infrastructure Agents Can Trust — join our mission to deliver the governed context layer that AI agents depend on: accurate semantic definitions, traceable lineage, data contracts, and auditable history baked in from the start.
- Embraces Open Standards — help build portable, interoperable data infrastructure: Agents Schema, open formats (Iceberg, Delta Lake), MCP\-native interfaces, and connector skills that work with any model and any compute.
- Scales Without Breaking — work to make Fivetran AI efficient at agent scale, where unit costs deflate as volume grows and context retrieval is fast, accurate, and cost\-controlled.
We emphasize using no\-nonsense tools and take great pride in the simplicity and effectiveness of the systems we build. Our back\-end is built on Java, Python, Postgres, and Kubernetes, and our front\-end is built on React and TypeScript.
This is a full\-time hybrid position based out of our New York, NY office. Our hybrid work model offers a blend of remote flexibility and in\-person collaboration, including two days in the office each week to connect and build as a team
Technologies You'll Use
Python, Java, SQL, dbt, LLMs (Claude, ChatGPT, Gemini), vector databases, BigQuery / Snowflake / Databricks, MCP protocol, React, TypeScript, Kubernetes
What You'll Do
- Identify which emerging AI research and techniques are worth pursuing, and set the agenda for Fivetran AI's technical roadmap accordingly
- Prototype new ideas quickly, then take the ones that prove out and turn them into shipped, production\-grade features
- Define technical direction that spans Fivetran AI and collaborating departments — product, data platform, and go\-to\-market — resolving architectural tradeoffs that cross department lines
- Build and maintain both back\-end and front\-end systems for the Fivetran AI product — from Agents Schema pipelines to the Context Catalog UI
- Set the long\-term technical vision for capabilities like AISQL: natural language to SQL grounded in dbt metric definitions, executed natively against the warehouse
- Take ownership of production reliability across the platform: on\-call rotation, incident response, and SRE work to keep the system trustworthy at scale
- Set the bar for engineering quality, testing, and QA practices across the department, and do hands\-on work yourself when it matters most
- Use coding agents to automate the repetitive parts of the job, freeing up time for the research and design work that needs a human
- Define your own priorities and roadmap based on your judgment of what will most move Fivetran AI forward, with minimal oversight
- Mentor staff and senior engineers, and act as a multiplier for technical judgment across the department
- Represent Fivetran AI's technical perspective in cross\-department planning and strategy discussions
- Contribute to hiring by participating in and helping shape the interview process
Skills We're Looking For
- 10\+ years of programming experience across Python and/or Java, with the ability to move fluidly between back\-end and front\-end work
- Considered a trusted expert beyond your own department, able to exert influence and shape direction with collaborating departments
- Comfortable reading AI/ML research and turning promising findings into working prototypes, then production systems, at a level that sets direction for others
- Deep product and market awareness — able to judge which emerging techniques are worth building versus which are hype, and defend that judgment to skeptical stakeholders
- Track record of defining your own direction and executing it with the highest level of independence, with little need for oversight
- Experience with SQL and data warehouses (BigQuery, Snowflake, Databricks, or similar)
- Genuine willingness to work across the full stack: research, backend, frontend, SRE, and QA, as the team's needs demand
- Writes well\-structured, performant code and can dive into unfamiliar codebases to suggest improvements
- Experience using coding agents or similar AI tooling to speed up day\-to\-day engineering work
- Demonstrated ability to mentor senior and staff engineers and influence technical decisions across departments
- Thrives in a startup\-like environment with shifting priorities and a high degree of ownership
Bonus Skills
- Experience with LLM\-powered applications — RAG pipelines, embeddings, evaluation frameworks, or agent frameworks
- Familiarity with semantic layers — dbt, LookML, Sigma, or similar
- Experience with the MCP (Model Context Protocol) ecosystem or building AI agent integrations
- Background in site reliability engineering — monitoring, alerting, incident response
- Experience in data processing (ETL, ELT) and/or building data connectors
- Experienced working in a cloud environment utilizing AWS, GCP, Kubernetes, or Docker
- Contributions to open source AI or data projects
\#LI\-HYBRID \#LI\-AM1
Perks and Benefits
- 100% employer\-paid medical insurance\*
- Generous paid time\-off policy (PTO), plus paid sick time, inclusive parental leave policy, holidays, and volunteer days off
- RSU stock grants\*
- Professional development and training opportunities
- Company virtual happy hours, free food, and fun team\-building activities
- Monthly cell phone stipend
- Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self\-guided mindfulness exercises for all covered employees and their covered dependents.
- *May vary by country and worker type \- please reach out to your recruiter for more information*
*Click* *here* *to learn more about Fivetran's Benefits by Region.*
We're honored to be valued at over $5\.6 billion, but more importantly, we're proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream. Read about us in Forbes.
Fivetran brings together high\-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion \& belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world\-class company to better serve our customers, our people and our communities.
To learn more about Fivetran's culture and what it's like to be part of the team, click here and enjoy our video.
To learn more about our candidate privacy policy, you can read our statement here.
*We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this* *form**. We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.*
Salary Context
This $232K-$290K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Fivetran, 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 $219,250 based on 424 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($261K) sits 19% above the category median. Disclosed range: $232K to $290K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Fivetran AI Hiring
Fivetran has 4 open AI roles right now. They're hiring across AI Software Engineer, Data Scientist. Positions span New York, NY, US, Chicago, IL, US. Compensation range: $209K - $290K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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