AI Software Engineer

$115K - $137K Dallas, TX, US Mid Level AI Software Engineer

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Skills & Technologies

AwsAzureCrewaiDockerFaissGcpHugging FaceKubernetesLangchainLlamaindex

About This Role

AI job market dashboard showing open roles by category

### Description

At Hallmark Health Care Solutions, what we do and how we do it go hand in hand. We bring a relentless focus to both our products and our people—grounded in curiosity, a bias for action, accountability and ownership, strong judgment, and a willingness to challenge the status quo in pursuit of better outcomes.

Hallmark Health Care Solutions is led by passionate experts with an average of 20\+ years’ experience in IT, nursing, process engineering, finance, and healthcare. We are committed to strengthening communities by producing technologies, support services, and thought leadership that tangibly improve patient care and community health outcomes.### What You’ll Do

We are looking for a highly capable and hands\-on AI Engineer to join our growing engineering and product innovation team. The ideal candidate should be able to understand complex business and AI requirements, architect practical AI\-driven solutions, collaborate with technical leads and managers, and independently deliver production\-grade AI initiatives.

What We Are Looking For

  • Someone who can think beyond demos and build AI systems that work reliably in real\-world production environments.
  • A self\-driven engineer who can take ownership of AI initiatives with minimal supervision.
  • A strong collaborator who can work effectively with leadership, managers, architects, and distributed engineering teams.
  • An individual passionate about solving meaningful business problems using practical AI innovation.

AI Solution Design \& Delivery* Understand business problems and translate them into scalable AI/ML and Generative AI solutions.

  • Design, develop, and deploy enterprise\-grade AI systems with a strong focus on reliability, scalability, monitoring, and measurable outcomes.
  • Lead or contribute to multiple AI initiatives simultaneously while coordinating with engineering leads, product managers, architects, and offshore teams.
  • Independently drive proof\-of\-concepts, pilots, and production implementations.

Agentic AI \& LLM Systems* Design and implement Agentic AI workflows capable of multi\-step reasoning, orchestration, task automation, and intelligent decision support.

  • Build AI agents using frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, MCP, or equivalent orchestration platforms.
  • Implement memory management, evaluation pipelines, guardrails, failure recovery, and observability for production AI systems.
  • Develop prompt engineering strategies and optimize LLM interactions for enterprise use cases.

RAG \& Semantic Search* Build scalable Retrieval\-Augmented Generation (RAG) systems including:

  • Document ingestion pipelines
  • Chunking strategies
  • Embedding generation
  • Vector databases
  • Hybrid semantic and keyword retrieval
  • Re\-ranking pipelines
  • Citation traceability
  • Work with vector stores such as FAISS, Pinecone, Weaviate, or similar technologies.
  • Implement evaluation frameworks to measure retrieval quality and response accuracy.

AI/ML Engineering* Develop and optimize ML and Deep Learning models for predictive analytics, classification, forecasting, NLP, computer vision, and recommendation systems.

  • Work with modern ML frameworks such as PyTorch, TensorFlow, Scikit\-learn, XGBoost, and Hugging Face.
  • Participate in model fine\-tuning, instruction tuning, RLHF, LoRA, and PEFT initiatives where applicable.

Cloud, MLOps \& Engineering Excellence* Build scalable AI infrastructure on cloud platforms such as Azure, AWS, or GCP.

  • Implement MLOps best practices including CI/CD pipelines, model monitoring, experiment tracking, infrastructure automation, and deployment orchestration.
  • Work with tools such as Docker, Kubernetes, Terraform, MLflow, Airflow, and GitHub Actions.
  • Optimize infrastructure usage, performance, and operational cost.

Collaboration \& Leadership* Work closely with onsite and offshore engineering teams to ensure smooth delivery and communication.

  • Collaborate with technical leads, architects, QA teams, DevOps teams, and product stakeholders.
  • Mentor junior engineers and contribute to AI capability building within the organization.

### What We’re Looking For

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or related field.
  • 6\+ years of software engineering experience with at least 3\+ years focused on AI/ML and Generative AI initiatives.
  • Hands\-on experience building and deploying production AI systems.
  • Experience delivering AI initiatives independently in enterprise environments.
  • Understanding of LLMs, Agentic AI architectures, and RAG systems.
  • Python programming skills and experience with APIs, distributed systems, and data engineering concepts.
  • Experience working in onsite/offshore collaboration models.
  • Excellent communication, analytical thinking, and problem\-solving skills.

Preferred Skills* Experience in Healthcare, Workforce Management, Staffing, Compliance, or Enterprise SaaS domains.

  • Exposure to AI governance, compliance, security, and responsible AI practices.
  • Experience with Computer Vision, NLP, forecasting, or healthcare AI use cases.
  • Knowledge of HIPAA\-compliant AI solution development is a plus.
  • Exposure to AI evaluation frameworks such as LangSmith, RAGAS, or equivalent.
  • Experience integrating AI solutions with enterprise platforms and third\-party systems.

### The Perks

  • Medical, Dental, and Vision Insurance with Employee Premiums Covered by HHCS at 100% and Company Cost Share for any Dependents Enrolled
  • $3000 Annual Company Contributions to HSAs for all Employees Enrolled in the HSA Eligible Health Plan
  • Unlimited Paid Time Off
  • Pre\-Tax and Roth 401(K) Retirement Options
  • On\-Site Gym, Free Parking, and Provided Lunches 3 Times per Week in the Dallas Office!

Hallmark Health Care Solutions, Inc is an Equal Opportunity Employer. All employment decisions are based on business needs, job requirements and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex, age, physical, mental or sensory disability, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. HHCS reserves the right to amend the job description, duties or qualifications based on company needs.

By applying to Hallmark Health Care Solutions, your application and all supplemental information is subject to our Privacy Policy. When clicking “Apply”, you will be redirected to our Applicant Tracking System, Pinpoint.

### About Hallmark Health Care Solutions

We specialize in delivering innovative solutions and exceptional services to meet the diverse needs of our clients. With a strong commitment to quality and customer satisfaction, we strive to exceed expectations and drive success in every project we undertake.

Salary Context

This $115K-$137K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).

Role Details

Title AI Software Engineer
Location Dallas, TX, US
Category AI Software Engineer
Experience Mid Level
Salary $115K - $137K
Remote No

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 hallmark health care solutions, 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

Aws (28% of roles) Azure (22% of roles) Crewai (3% of roles) Docker (10% of roles) Faiss (1% of roles) Gcp (15% of roles) Hugging Face (3% of roles) Kubernetes (13% of roles) Langchain (9% of roles) Llamaindex (3% of roles)

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. This role's midpoint ($126K) sits 42% below the category median. Disclosed range: $115K to $137K.

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.

hallmark health care solutions AI Hiring

hallmark health care solutions has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Dallas, TX, US. Compensation range: $137K - $137K.

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

Based on 729 roles with disclosed compensation, the median salary for AI Software Engineer positions is $218,500. Actual compensation varies by seniority, location, and company stage.
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.
About 15% of the 4,317 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
hallmark health care solutions is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI Software Engineer positions include Staff Engineer, AI Architect, Engineering Manager. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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