[Remote] AI/LLM Evaluation & Alignment Software Engineer

🌍 Remote, USA 🚀 Full-time 🕐 Posted Recently

Job Description

Note: The job is a remote job and is open to candidates in USA. LeoTech is passionate about building software that solves real-world problems in the Public Safety sector. The AI/LLM Evaluation & Alignment Software Engineer will ensure that Large Language Model (LLM) and Agentic AI solutions are accurate and aligned with public safety workflows by designing evaluation frameworks and implementing bias-mitigation strategies.

Build and maintain evaluation frameworks for LLMs and generative AI systems tailored to public safety and intelligence use cases
Design guardrails and alignment strategies to minimize bias, toxicity, hallucinations, and other ethical risks in production workflows
Partner with AI engineers and data scientists to define online and offline evaluation metrics (e.g., model drifts, data drifts, factual accuracy, consistency, safety, interpretability)
Implement continuous evaluation pipelines for AI models, integrated into CI/CD and production monitoring systems
Collaborate with stakeholders to stress test models against edge cases, adversarial prompts, and sensitive data scenarios
Research and integrate third-party evaluation frameworks and solutions; adapt them to our regulated, high-stakes environment
Work with product and customer-facing teams to ensure explainability, transparency, and auditability of AI outputs
Provide technical leadership in responsible AI practices, influencing standards across the organization
Contribute to DevOps/MLOps workflows for deployment, monitoring, and scaling of AI evaluation and guardrail systems (experience with Kubernetes is a plus)
Document best practices and findings, and share knowledge across teams to foster a culture of responsible AI innovation

Bachelor's or Master's in Computer Science, Artificial Intelligence, Data Science, or related field
3–5+ years of hands-on experience in ML/AI engineering, with at least 2 years working directly on LLM evaluation, QA, or safety
Strong familiarity with evaluation techniques for generative AI: human-in-the-loop evaluation, automated metrics, adversarial testing, red-teaming
Experience with bias detection, fairness approaches, and responsible AI design
Knowledge of LLM observability, monitoring, and guardrail frameworks e.g Langfuse, Langsmith
Proficiency with Python and modern AI/ML/LLM/Agentic AI libraries (LangGraph, Strands Agents, Pydantic AI, LangChain, HuggingFace, PyTorch, LlamaIndex)
Experience integrating evaluations into DevOps/MLOps pipelines, preferably with Kubernetes, Terraform, ArgoCD, or GitHub Actions
Understanding of cloud AI platforms (AWS, Azure) and deployment best practices
Strong problem-solving skills, with the ability to design practical evaluation systems for real-world, high-stakes scenarios
Excellent communication skills to translate technical risks and evaluation results into insights for both technical and non-technical stakeholders

3 weeks of paid vacation – out the gate!!
Generous medical, dental, and vision plans.
Sick, and paid holidays are offered.

LeoTech is leading the effort to assist public safety efforts around the nation. It was founded in 2018, and is headquartered in Los Angeles, California, USA, with a workforce of 51-200 employees. Its website is https://leotechnologies.com.

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