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Description:
AI SOFTWARE ENGINEER Location: REMOTE
Rajant Health Incorporated (RHI) is building a healthcare assurance ecosystem to enable proactive and personalized health. We provide personalized health insights that improve diagnostics, therapeutics, communication, and the overall patient experience.
Our monitoring solutions, data integration, and advanced analytics transform raw data into actionable insights for clinical, biomedical, and research applications. Our portfolio includes Cowbell®, Q\-Stat®, and Trovomics®—innovative technologies supporting large animal monitoring, remote health management, biomarker identification, and next\-generation health discovery.
Based in Malvern, Pennsylvania, RHI develops intelligent healthcare technologies that make complex health data understandable and actionable for researchers, healthcare providers, and individuals.
Backed by our parent company, Rajant Corporation, with more than 25 years of innovation in intelligent edge networking and mission\-critical connectivity, RHI is advancing the future of connected healthcare through AI, edge computing, and real\-time health intelligence. For more information, visit RajantHealth.com or follow Rajant Health on LinkedIn and YouTube.
POSITION OVERVIEW:
Rajant Health is seeking a Software Engineer to own the development of our polling technology products. The work spans statistical estimation of survey results, development of the interactive applications that present them, and AI\-assisted analysis of open\-ended responses.
KEY RESPONSIBILITIES:
*Statistical Modeling*
- Maintain and extend the pipeline that turns raw survey data into weighted, model\-based estimates.
- Construct population targets, apply survey weighting, and fit and validate regression models.
- Ensure published methodology matches what is computed.
*Data Visualization*
- Own the client\-facing applications that present survey results.
- Manage the flow of estimates and geographic data from pipeline to publication.
- Deploy and operate these applications.
*AI\-Assisted Analysis*
- Own the pipeline that applies large language models to open\-ended survey responses.
- Develop and evaluate prompts; monitor output quality and cost.
- Produce client\-ready interactive reports.
*Engineering Practice*
- Bring testing, automation, and documentation to actively developed codebases.
- Explain technical and methodological decisions clearly.
REQUIRED QUALIFICATIONS:
- 5\+ years of professional software engineering experience.
- Strong programming ability in multiple languages and the versatility to pick up new ones.
- Applied statistics experience: regression modeling, survey weighting, and model validation.
- Experience building applications on large language models, including systematic prompt evaluation.
- Experience building, deploying, and operating data\-driven web applications.
- Demonstrated independent ownership of production systems.
PREFERRED QUALIFICATIONS:
- Geographic and polling data analysis experience.
- Bayesian modeling experience.
- Familiarity with government statistical data sources.
CANDIDATE PROFILE:
The ideal candidate combines software engineering fundamentals with applied statistics and assumes ownership of what they build.
WHY JOIN RAJANT HEALTH:
- Build innovative AI\-powered healthcare and financial technology solutions that improve customer experiences and business outcomes.
- Work alongside engineers, AI specialists, clinicians, and business leaders solving meaningful technical challenges.
- Develop next\-generation intelligent software using modern AI, cloud, and distributed computing technologies.
- Help shape the future of connected healthcare, intelligent financial services, and data\-driven decision\-making.
- Join an innovative organization backed by Rajant Corporation's engineering expertise and commitment to advancing technology.
READY TO BUILD WHAT’S NEXT?
If you're passionate about building production AI applications that transform healthcare and financial services, we'd love to hear from you. Apply Today.
Employment Type: Full\-Time with Benefits.
Location: Remote.
Apply: Please send cover letter and resume to [email protected].
*Rajant* *Corporation* *is* *an* *Equal Opportunity* *Employer* *and* *does* *not* *discriminate on* *the basis* *of race, color, religion, gender, national origin, age,* *physical or mental impairment, sexual orientation or any other category protected under federal, state or* *local law. Rajant is* *a USG* *Contractor* *and complies with all US laws, regulations and Executive Orders.*
Requirements:
REQUIRED QUALIFICATIONS:·
- 5\+ years of professional software engineering experience.
- Strong programming ability in multiple languages and the versatility to pick up new ones.
- Applied statistics experience: regression modeling, survey weighting, and model validation.
- Experience building applications on large language models, including systematic prompt evaluation.
- Experience building, deploying, and operating data\-driven web applications.
- Demonstrated independent ownership of production systems.
PREFERRED QUALIFICATIONS:
- Geographic and polling data analysis experience.
- Bayesian modeling experience.
- Familiarity with government statistical data sources.
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 Rajant Corporation, 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 in Demand for This Role
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. Mid-level AI roles across all categories have a median of $194,400.
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.
Rajant Corporation AI Hiring
Rajant Corporation has 1 open AI role right now. They're hiring across AI Software Engineer. Based in US.
Location Context
AI roles in Austin pay a median of $214,343 across 143 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 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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