Lead AI/ML Engineer

Team: IT

Location: US

Commitment: Full-time

Workplace Type: remote

Accountabilities

• Design, build, and optimize enterprise AI solutions, including RAG, semantic retrieval, model orchestration, and AI-powered decision-support capabilities.

• Develop and maintain model-serving infrastructure, embedding services, vector search platforms, and inference pipelines for scalable production workloads.

• Create AI evaluation frameworks and testing methodologies covering model accuracy, groundedness, response quality, reliability, and business performance.

• Implement AI governance, security, and guardrail mechanisms, including PII protection, prompt-injection defenses, access controls, monitoring, and compliance controls.

• Partner with data engineering teams to integrate governed data sources, semantic layers, and structured-query frameworks that support trustworthy and explainable AI outputs.

• Collaborate with product, platform, security, engineering, and business stakeholders to define AI capabilities, improve performance, and continuously enhance solution effectiveness.

• Provide technical leadership and help establish engineering practices that support reliable, maintainable, and production-ready AI systems.

Requirements

• 6+ years of professional software engineering experience, including at least 2 years building and deploying production AI, machine learning, NLP, LLM, or RAG solutions.

• Strong proficiency in Python and modern AI/ML frameworks, with demonstrated experience developing scalable, production-grade AI applications and services.

• Hands-on expertise with LLM technologies, including model serving, vector databases, embeddings, prompt engineering, retrieval pipelines, agent and tool orchestration, and AI workflow automation.

• Practical experience implementing AI governance and security controls, including model evaluation, guardrails, PII protection, prompt-injection prevention, access management, and responsible AI practices.

• Strong software engineering fundamentals and the ability to design dependable AI systems that can operate at enterprise scale.

• Excellent communication and collaboration skills, with the ability to work effectively across data, platform, product, security, engineering, and business functions.

• Preferred experience with self-hosted or open-weight models, vLLM, Ollama, Qdrant, pgvector, LlamaIndex, Haystack, semantic layers, financial services, or other highly regulated industries.

Benefits

• Fully remote position within the United States.

• Opportunity to lead enterprise-scale generative AI and machine learning initiatives.

• Exposure to advanced technologies spanning LLMs, RAG, vector search, model serving, AI orchestration, and responsible AI.

• Cross-functional collaboration with data, platform, product, security, engineering, and business teams.

• Opportunity to shape AI architecture, governance, evaluation, and production engineering practices.

• Work in complex enterprise environments where security, reliability, explainability, and compliance are core priorities.

• Professional growth through ownership of technically challenging AI initiatives and emerging technologies.