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About This Role
At Bloomerang, we believe change happens on purpose. We champion the power and potential of nonprofits, igniting next\-level impact with the team and technology built for purpose. Our powerful giving platform and stellar support enable tens of thousands of nonprofits to raise more, recruit more, and retain more, fueling maximum impact and raising the bar on what's possible for the nonprofit sector. That's why, even as the nonprofit sector sees declines in giving, Bloomerang customers raise more year over year.
We're also in the business of creating thriving employees. Join a mission\-driven culture built on our core values of Simplify, Care and Act. We know our people are the key to our success, and we're proud to be home to some of the most innovative and skilled individuals in the workforce today. Come feel invigorated and unstoppable with us!
The Role
As a Sr. Software Engineer on the Platform Engineering team at Bloomerang, you build and own the AI harness our engineering organization runs on—the agentic tooling, orchestration, and evaluation infrastructure that turns frontier models into reliable, everyday engineering leverage in service of our mission to empower nonprofits. You go deep on what makes AI\-driven development trustworthy at scale: agent workflows and guardrails, tool and model integrations, prompt and context pipelines, and evals. And you help us use the throughput that unlocks the way it should be used—not just shipping faster, but following through on delivery with real customer feedback, measurement, and iteration until the work makes a meaningful difference for nonprofits. In the near term you'll also strengthen the systems the platform depends on—our authentication chain (centralized authentication and session management) as we drive toward a unified identity solution, primarily in C\#/.NET. But your throughline is the harness: you make every engineer around you faster, and you raise the bar for how Bloomerang builds with AI.
What You Will Do
- Build and own the agentic harness Bloomerang engineering runs on—agent workflows, tool and model integrations, orchestration, and the guardrails and evaluation infrastructure that keep AI\-driven development reliable and safe.
- Use the throughput AI\-driven development unlocks to follow through on delivery—ship minimum viable increments, then gather real customer feedback, run A/B tests, measure what shipped, and iterate until it makes a meaningful difference for nonprofits. The work doesn't stop at the MVP; we use the time AI gives back to deliver the functionality, quality, security, and the rest of the \-ilities our industry has always wanted to and rarely had time for.
- Own cross\-cutting AI\-platform concerns while standardizing prompt and context pipelines and consolidating local development environments across our products and teams. Keeping token spend efficient without ever trading away quality or completeness.
- Continually evaluate new models, AI tools, harnesses, and approaches—running rigorous evals and turning the winners into paved\-road tooling the whole organization can rely on.
- Design, build, and own backend services at the core of our platform—in the near term, our authentication chain (centralized authentication and session management), advancing toward a unified identity solution, primarily in C\#/.NET.
- Diagnose and resolve complex technical bottlenecks across distributed services and the AI tooling that sits on top of them, leveraging deep knowledge of debugging and observability tools to keep our SaaS platform fast and reliable.
- Improve the engineering standards, automation, developer tooling, and AI harness the team relies on.
- Help the team deliver in a continuous\-flow (Kanban) model—keeping work moving, surfacing bottlenecks, and continuously improving how we work, including collaborative practices like mob (ensemble) programming.
- Use your experience to shape our software and delivery tooling—raising the bar on engineering standards, teaching and learning alongside the organization, and helping us ship better products for the nonprofits we serve.
- Actively explore, integrate, and help lead the responsible use of AI across the team—shaping Bloomerang's AI culture as we lean into it.
What You Need to Succeed
- Genuine AI fluency and hands\-on experience building with AI—agents, tools, harnesses, prompt and context pipelines, or evals—not just using AI to code faster.
- 8\+ years of professional software engineering experience building and operating production services—or equivalent demonstrated depth.
- Strong C\#/.NET proficiency is ideal but not a deal breaker. We care most about your ability to own backend services end to end and ramp quickly on our stack; familiarity with the agentic\-tooling ecosystem (model APIs, MCP, LLM orchestration) is a strong plus.
- Experience with foundational platform or distributed systems; authentication, identity, security, MFA, SSO, or session management is a plus.
- A self\-directed, senior\-level ownership mindset: you can take an ambiguous problem and drive it to a shipped, reliable solution.
- Model high standards of technical excellence, ownership, and continuous learning.
- Ability to own the quality of your work end to end. You are accountable for what you ship and you raise the quality bar for the codebases and tooling you touch.
- Proficiency across a diverse range of frameworks, languages, databases, and tools; strength in C\#/.NET is ideal, and comfort in the Python/TypeScript that agentic tooling often lives in is a plus.
- Collaborative mindset while partnering with Product, DevOps, and across Engineering to solve broad infrastructure and platform problems. Responsible for designing and delivering solutions that are scalable, maintainable, reliable, and secure.
Benefits
Health \+ Wellness
You'll have access to generous health, vision, and dental insurance options as well as HealthiestYou, a healthcare service that offers convenient, confidential access to quality doctors 24/7, anytime, anywhere.
Time Off
You'll get a competitive PTO package that includes 20 PTO days, 3 flex days, 4 optional volunteer days, 12 paid holidays, as well as paid parental leave. More is more!
401k
You'll receive a 401k match to help invest in your future.
Equipment
Everything you need to be successful, shipped right to your door. You got this. We got you.
Compensation
The salary range for this position is $114,800 \- $191,400\. You may also be eligible for a discretionary bonus. Actual compensation within the range will be dependent on your skills, experience, qualifications, and location, as well as applicable employment laws
Location
This is a permanent, full\-time, fully remote position (within the U.S. and select Canadian Provinces only). Employees living in Indianapolis, IN are welcome to work from our company headquarters. We do not offer Visa sponsorship or relocation assistance at this time.
Accommodations
Applicants who require accommodations may contact [email protected] to request an accommodation in completing an application.
*Bloomerang is an Equal Opportunity Employer. Individuals seeking employment at Bloomerang are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.*
Salary Context
This $114K-$191K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $185K across 231 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 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Bloomerang, 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. This role's midpoint ($153K) sits 30% below the category median. Disclosed range: $114K to $191K.
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.
Bloomerang AI Hiring
Bloomerang has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US. Compensation range: $191K - $191K.
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.
Frequently Asked Questions
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