AI Software Engineer

Hallmark Health Care SolutionsDallas, TX
$115,000 - $137,500Remote

About The Position

Hallmark Health Care Solutions is seeking a highly capable and hands-on AI Engineer to join their growing engineering and product innovation team. The ideal candidate will be responsible for understanding complex business and AI requirements, architecting practical AI-driven solutions, collaborating with technical leads and managers, and independently delivering production-grade AI initiatives. The role requires an individual who can build AI systems that work reliably in real-world production environments, take ownership of AI initiatives with minimal supervision, and collaborate effectively with leadership, managers, architects, and distributed engineering teams. The position focuses on solving meaningful business problems using practical AI innovation.

Requirements

  • 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.

Nice To Haves

  • 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.

Responsibilities

  • 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.
  • 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.
  • 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, and citation traceability.
  • Work with vector stores such as FAISS, Pinecone, Weaviate, or similar technologies.
  • Implement evaluation frameworks to measure retrieval quality and response accuracy.
  • 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.
  • 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.
  • 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.

Benefits

  • 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!
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