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About This Role
About ColigoMed
ColigoMed is a healthcare AI company automating the administrative work that slows down specialty care. Our agentic AI platform delivers touchless eligibility and benefits verification, autonomous prior authorization with EMR write-back, integrated care program enablement (RPM, CCM, PCM, TCM), and hospital readmission reduction, supported by a patient app and a provider app. We are live with 50+ paying customers across cardiology, pulmonology, and pain management and backed by an $8M seed round from 70+ physicians.
Your Role
You will be focused on building, improving and supporting cutting-edge AI-enabled digital health technology across patient and provider workflows. You will work across the full software development lifecycle, including solution design, coding, testing, deployment and production support. The role involves APIs, microservices, data flows, AI/agentic workflows and healthcare integrations, applying modern technologies to real-world healthcare problems.
Working closely with engineering, product, clinical operations and QA, you will help deliver reliable, scalable and secure solutions. The role suits an engineer who has a background in the healthcare technology and enjoys solving complex problems, taking ownership of defined work and continuing to develop their skills in modern software engineering and AI technologies.
Availability & Work Authorization
You must be based in either the Central or Eastern Time Zone and be available to work 8:00 AM to 5:00 PM ET. This role also includes participation in an on-call rotation program. Applicants must be authorized to work in the United States without current or future employer sponsorship. ColigoMed is unable to provide employment visa sponsorship for this position.
What you will do
Engineering Delivery
● Participate in sprint planning, design and solution reviews, and feature delivery.
● Cover the full software lifecycle, including requirements, design, coding, testing, deployment and maintenance.
● Develop microservices and agent workflows with high standards for performance, scalability, availability and security.
● Improve observability across our solutions through logging, tracing, dashboards and alerting so failures can be detected before customers report them.
● Collaborate with product, care teams and QA to deliver high-quality products.
● Apply AI-driven engineering practices, including spec-driven development and agentic development workflows.
● Document root causes, fixes and playbooks so knowledge is shared across the team rather than held by one person.
● Share knowledge with other engineers on debugging, supportability and technical best practices.
Production and Customer Support
● Act as a technical problem solver across our integrated care solutions, including prior authorization (PA).
● Take ownership of customer and production support issues, including triaging, root-causing and resolving failed or stuck workflows, integration and data errors, payer or EHR connection problems, RPA breakages and performance regressions.
● Resolve issues within agreed severity levels, response targets & participate in an on-call rotation.
● Turn recurring issues into permanent platform improvements through code changes, automated tests, evaluations, runbooks and monitoring rather than one-off patches.
● Feed customer-specific fixes back into the shared platform so each resolution can benefit other products, specialties and customers.
● Work directly with product, clinical operations, customer success and support teams to clarify problems and communicate status clearly.
What you bring
● Bachelor’s degree in Computer Science or a closely related field.
● 3+ years of hands-on software development experience including healthcare technology experience with debugging, troubleshooting and problem-solving skills in production systems.
● Full-stack development experience with strong backend capabilities building REST APIs and microservices using Node.js and Python, along with good knowledge of ReactJS and TypeScript.
● Hands-on experience building LLM-based or agentic workflows, for example using LangChain, LangGraph, tool use or MCP, incl prompt design, observability & evaluation of LLM outputs.
● Solid knowledge of SQL, preferably PostgreSQL, and NoSQL technologies such as MongoDB, Elasticsearch or Neo4j, together with data modeling experience.
● Experience with messaging and caching technologies such as Kafka and Redis, and cloud-based deployment using technologies such as AWS, Docker and Kubernetes.
● Experience with browser or portal automation using RPA, Playwright or similar technologies, including diagnosing and resolving automation failures.
● Working knowledge of the healthcare industry is a prerequisite, ideally including prior authorization or related payer-provider workflows.
● Comfortable with ambiguity, changing priorities and taking ownership of defined outcomes in a fast-moving environment.
● Able to work effectively in global Agile teams and participate in an on-call rotation as required.
Compensation & Benefits
Base salary: $90,000 to $105,000 depending on experience, technical capability and location. Annual bonus: Discretionary bonus of up to 10% of base salary, subject to company and individual performance. Equity: Eligibility to participate in ColigoMed’s stock option program.
Additional employee benefits are provided in accordance with the company’s benefit programs.
Pay: $90,000.00 - $105,000.00 per year
Benefits:
- 401(k)
- Dental insurance
- Dependent health insurance coverage
- Disability insurance
- Health insurance
- Paid holidays
- Paid sick time
- Paid time off
- Referral program
- Vision insurance
- Work from home
Application Question(s):
- Do you have a working knowledge of the healthcare industry ideally including prior authorization or related payer-provider workflows. Yes or No
- Do you have hands-on experience building production backend services using Node.js and/or Python, including REST APIs or microservices? Yes or No
- Do you have hands-on experience building LLM-based or agentic workflows using tools such as LangChain, LangGraph, MCP or similar? Yes or No
- Do you have hands-on experience with browser/portal automation using Playwright, RPA or similar tools, including troubleshooting automation failures? Yes or No?
Experience:
- software development: 3 years (Required)
Work Location: Remote
Salary Context
This $90K-$105K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $194K across 269 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 11,520 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At ColigoMed, 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 $220,000 based on 1,688 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($97K) sits 56% below the category median. Disclosed range: $90K to $105K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
ColigoMed AI Hiring
ColigoMed has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Remote, US. Compensation range: $105K - $105K.
Remote Work Context
Remote AI roles pay a median of $188,200 across 2,430 positions. About 6% 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 Safety roles lead at $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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