Interested in this AI Software Engineer role at WellSky?
Apply Now →Skills & Technologies
About This Role
The Staff Software Engineer (AI Platform Engineer) is responsible for driving AI\-first engineering across WellSky by architecting and building agentic solutions, automating developer workflows, and enabling engineers and the Solutions organization to deliver faster and better. The scope of this job includes setting the technical direction for agentic AI development on the Engineering Enablement team, leading org\-wide enablement and training, and partnering with product engineering teams and the Solutions organization to integrate agentic workflows into the software development lifecycle and customer delivery processes.
Key Responsibilities:
- Architect and build agentic AI solutions — including autonomous workflows, tool\-calling agents, RAG pipelines, and LLM integrations — that are used daily by WellSky engineers and the Solutions organization.
- Set the technical direction for AI\-first engineering on the Engineering Enablement team, guiding the Senior Software Engineer and defining standards for agentic development, prompt engineering, context management, and LLM integration across WellSky repositories.
- Own the AI enablement platform: agent skills, CI/CD automation, developer tooling, and shared libraries that raise the productivity floor for the entire engineering organization.
- Lead training sessions, workshops, demos, and office hours that build AI\-first engineering skills and practices across WellSky’s engineering organization.
- Partner with the Solutions organization to identify opportunities and integrate agentic workflows into SDLC and customer\-facing delivery processes.
- Embed directly with product engineering teams to identify where agentic AI delivers real value, then build and hand off the tooling that makes adoption stick.
- Evaluate agent output quality, establish evaluation and observability practices, and ensure AI tooling is safe and reliable before rollout.
- Serve as WellSky’s internal authority on agentic AI development patterns, emerging tooling, and best practices.
- Write clear, high\-quality documentation, guides, and enablement materials consumed by hundreds of engineers.
- Collaborate with engineering leaders to prioritize the highest\-value AI enablement opportunities across the organization.
- Perform other job duties as assigned.
Required Qualifications:
- Bachelor’s degree in a related field, or equivalent work experience.
- 8\-12 years of relevant software engineering experience, with substantial depth in .NET / C\#.
- At least 2 years of hands\-on experience developing with LLMs, including a minimum of 1 year architecting and building agentic AI solutions — agentic workflows, tool/function calling, RAG, prompt and context engineering, and agent evaluation.
- Must have shipped agentic systems to production that are used by real users; prototypes and proofs of concept alone do not meet this bar.
- Strong, current .NET / C\# skills (.NET 8 or newer, ASP.NET Core); must be able to work directly in WellSky’s .NET codebases and embed with .NET product teams.
- Proficiency in Python, the primary language for AI tooling, agent platforms, and data pipelines on this team.
- Experience building internal developer tools, CI/CD automation, or shared libraries for other engineers — not just product features.
- Hands\-on experience integrating LLM APIs (Anthropic, OpenAI, or Vertex AI), including tool/function calling and streaming at production scale.
- Daily use of AI\-assisted development tools such as Claude Code, GitHub Copilot, or Cursor.
- Demonstrated ability to lead technical direction, guide senior engineers, and drive adoption of new practices across a team or organization.
- Excellent written communication skills; comfortable producing documentation and enablement materials for a large technical audience.
- Comfortable running training, demos, and office hours for engineers at all levels.
Preferred Qualifications:
- TypeScript / JavaScript proficiency; React experience strongly preferred.
- Experience with event\-driven messaging systems — Apache Kafka, Google Pub/Sub, Azure Service Bus, or RabbitMQ (Kafka is the standard on our go\-forward platform).
- Experience with Model Context Protocol (MCP) — building MCP servers, clients, and agent integrations (strong differentiator).
- PostgreSQL and vector database experience — pgvector, Pinecone, Weaviate, or Vertex AI Search.
- Google Cloud Platform experience — Cloud Run, Vertex AI, GKE (Azure or AWS also considered).
- LLM evaluation and observability experience — evals, tracing, prompt regression testing.
- Familiarity with agent and LLM frameworks such as Claude Agent SDK, Semantic Kernel, Microsoft.Extensions.AI, LangChain, or LangGraph.
- Domain\-Driven Design and CQRS experience (MediatR or equivalent).
- OpenTelemetry and distributed tracing experience — Jaeger, Seq, Datadog, or Grafana.
- Experience guiding or mentoring senior engineers.
- Healthcare industry experience preferred; HIPAA and PHI handling experience weighted highly.
- Consulting instinct — able to embed with a team, diagnose where AI actually helps, and say no clearly where it does not.
- High tolerance for ambiguity and a fast\-moving tooling landscape.
Job Expectations:
- Willing to work additional or irregular hours as needed
- Must work in accordance with applicable security policies and procedures to safeguard company and client information
- Must be able to sit and view a computer screen for extended periods of time
\#LI\-TC1
\#LI\-Remote
WellSky is where independent thinking and collaboration come together to create an authentic culture. We thrive on innovation, inclusiveness, and cohesive perspectives. At WellSky you can make a difference.
Here are some of the exciting benefits full\-time teammates are eligible to receive at WellSky:
- Excellent medical with Rx, dental, and vision benefits
- Mental Health support through EAP
- Generous paid time off, plus 13 paid holidays
- 100% vested 401(K) retirement plans
- Educational assistance up to $2500 per year
WellSky provides equal employment opportunities to all people without regard to race, color, national origin, ancestry, citizenship, age, religion, gender, sex, sexual orientation, gender identity, gender expression, marital status, pregnancy, physical or mental disability, protected medical condition, genetic information, military service, veteran status, or any other status or characteristic protected by law. WellSky is proud to be a drug\-free workplace.
Applicants for U.S.\-based positions with WellSky must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire. Certain client\-facing positions may be required to comply with applicable requirements, such as immunizations and occupational health mandates.
Data Privacy Notice for Job Applicants and Teammates
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 WellSky, 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.
WellSky AI Hiring
WellSky has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Overland Park, KS, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.