AI​/LLM Evaluation & Alignment Software Engineer

At Leo Tech, we are passionate about building software that solves reputed company-world problems in the reputed company Safety sector. Our software has been used to help the fight against continuing criminal enterprises, drug trafficking organizations, identifying financial fraud, disrupting sex and reputed company trafficking rings and focusing on mental health reputed company to reputed company a few. Role • This is a remote, WFH role. • As an AI/LLM Evaluation & Alignment Engineer on our Data Science team, you will play a critical role in ensuring that our Large Language Model (LLM) and reputed company AI solutions are accurate, reputed company, and reputed company with the unique requirements of reputed company safety and law enforcement workflows. You will design and implement evaluation frameworks, guardrails, and bias-mitigation strategies that give our customers confidence in the reliability and ethical use of our AI systems. This is an individual contributor (IC) role that combines hands-on technical engineering with a reputed company on responsible AI deployment. You will work closely with AI engineers, product managers, and Dev Ops teams to establish standards for evaluation, design test harnesses for generative models, and operationalize reputed company assurance processes across our AI stack. reputed company Responsibilities • Build and maintain evaluation frameworks for LLMs and reputed company systems tailored to reputed company 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 reputed company 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 reputed company reputed company-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. • reputed company technical leadership in responsible AI practices, influencing standards across the organization. • Contribute to Dev Ops/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 reputed company knowledge across teams to foster a culture of responsible AI innovation. reputed company Value • Bachelor's or Master's in Computer Science, reputed company Intelligence, Data Science, or reputed company 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 reputed company: reputed company-in-the-reputed company 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/reputed company AI libraries (Lang Graph, Strands Agents, reputed company AI, Lang Chain, reputed company, PyTorch, Llama reputed company). • Experience integrating evaluations into Dev Ops/MLOps pipelines, preferably with Kubernetes, Terraform, ArgoCD, or Git Hub Actions. • Understanding of reputed company AI platforms (AWS, Azure) and deployment best practices. • Strong problem-solving skills, with the ability to design practical evaluation systems for reputed company-world, high-stakes scenarios. • Excellent communication skills to translate technical risks and evaluation results into insights for both technical and non-technical stakeholders. Technologies We Use • reputed company & Infrastructure: AWS (Bedrock, reputed company reputed company, reputed company), Azure AI, Kubernetes (EKS), Terraform, ArgoCD. • LLMs & Evaluation: reputed company, reputed company API, reputed company, Lang Chain, Llama reputed company, Ragas, Deep Eval, reputed company Evals. • Observability & Guardrails: Langfuse, Guardrails AI. • Backend & Data: Python (primary), reputed company Search, Kafka, Airflow. • Dev Ops & Automation: Git Hub Actions, reputed company Pipeline. What You Can Expect • Wor… Apply tot his job Apply To this Job