AI Technical Lead at IANS

<p><span style="font-size: 18pt;"><strong>AI Technical Lead</strong></span></p> <p>Requires minimum of 2 days a week onsite in Boston, MA office</p> <p>$160,000 - $200,000 + bonus</p> <p><strong>About the Role</strong></p> <p>IANS is rapidly expanding its AI strategy toward a <strong>Data-as-a-Service (DaaS)</strong> model—delivering not only insights through our own applications, but also structured data feeds, APIs, and AI-ready interfaces that enable clients to build their own intelligent systems and agentic workflows.</p> <p>We are seeking a highly skilled <strong>AI Technical Lead</strong> to drive the design, development, and evolution of both our <strong>internal AI systems</strong> and our <strong>client-facing agent platforms</strong>. This role serves as the technical authority across AI initiatives—architecting agentic systems, building reusable frameworks, and guiding the engineering strategy that powers IANS’ next generation of data-driven products.</p> <p>You will own the full lifecycle of AI and ML systems, with deep expertise in LLMs, retrieval-augmented generation (RAG), agent design, and enterprise-grade architecture.</p> <p>&nbsp;</p> <p><strong>AI Architecture, Agent Systems &amp; DaaS Platform Development</strong></p> <ul> <li>Lead the design and development of <strong>AI agent systems</strong> aligned with IANS’ evolving DaaS strategy, enabling clients to consume IANS data feeds and build their own AI agents using proprietary, internal, and third-party data.</li> <li>Architect agentic workflows that orchestrate <strong>retrieval, reasoning, tool use, planning, and action execution</strong> across enterprise contexts.</li> <li>Develop <strong>reusable agent frameworks</strong>, primitives, and <strong>SDK-style abstractions</strong> that external clients can safely and flexibly extend for their own applications.</li> <li>Integrate <strong>RAG pipelines, tool use, APIs, and multi-agent patterns</strong> into robust, production-grade platforms.</li> <li>Define scalable abstractions for agent memory, tool orchestration, context management, and autonomous task execution.</li> </ul> <p>&nbsp;</p> <p><strong>Technical Leadership &amp; Strategy</strong></p> <ul> <li>Shape the long-term AI and agent-platform roadmap in partnership with product and engineering leaders.</li> <li>Serve as the primary subject-matter expert on <strong>agentic systems, LLM architectures, RAG, and DaaS platform design</strong>.</li> <li>Provide technical leadership and mentorship across AI initiatives, ensuring consistent engineering excellence.</li> <li>Evaluate emerging technologies, frameworks, and standards relevant to AI agents, data delivery, automation, and platform extensibility.</li> </ul> <p>&nbsp;</p> <p><strong>Software Engineering &amp; Systems Integration</strong></p> <ul> <li>Develop production-grade Python code using frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, and modern agent toolkits.</li> <li>Design and maintain APIs, microservices, and developer-facing interfaces that enable both internal and external teams to integrate with IANS’ data and agent platforms.</li> <li>Implement robust testing, observability, logging, and performance optimization for complex agent workflows and model-driven systems.</li> <li>Ensure compatibility between internal systems and externally consumed SDKs, tools, and data interfaces.</li> </ul> <p>&nbsp;</p> <p><strong>AI Infrastructure, Deployment &amp; MLOps</strong></p> <ul> <li>Architect and manage scalable cloud-based AI/agent infrastructure (Azure preferred).</li> <li>Implement MLOps pipelines for continuous delivery, safe model updates, monitoring, evaluation, and governance.</li> <li>Build and maintain data pipelines supporting RAG, retrieval, embeddings, agent memory, and inference.</li> <li>Establish observability frameworks for agent behavior, tool interactions, and cost management.</li> </ul> <p>&nbsp;</p> <p><strong>Security, Governance &amp; Enterprise-Grade Standards</strong></p> <ul> <li>Define and enforce strict standards for <strong>security, data isolation, governance, observability, and cost control</strong>, especially when exposing agent capabilities and data products to clients.</li> <li>Ensure safe sandboxing, permissioning, and policy enforcement for client-built AI agents.</li> <li>Oversee compliance with regulatory frameworks (GDPR, CCPA, etc.) and responsible AI practices including fairness, explainability, privacy, and risk mitigation.</li> </ul> <p>&nbsp;</p> <p><strong>Qualifications &amp; Skills</strong></p> <p><strong>Required</strong></p> <ul> <li>5+ years of experience in AI/ML engineering, with 2+ years in a senior or lead role.</li> <li>Hands-on experience designing <strong>agentic AI systems</strong>, AI agents, or multi-agent frameworks for production environments.</li> <li>Deep expertise with LLMs, NLP, RAG pipelines, embeddings, and generative AI technologies.</li> <li>Strong Python engineering skills; experience with PyTorch, TensorFlow, Hugging Face, LangChain, etc.</li> <li>Experience architecting APIs, SDKs, or developer-facing tools used by external customers.</li> <li>Strong understanding of distributed systems, cloud infrastructure (Azure preferred), and scalable architectures.</li> <li>Familiarity with MLOps workflows, CI/CD, model monitoring, evaluation, and lifecycle management.</li> <li>Strong communication, leadership, and cross-functional collaboration skills.</li> </ul> <p>&nbsp;</p> <p><strong>Nice to Have:</strong></p> <ul> <li>Experience with LoRA, PEFT, RLHF, and advanced fine-tuning techniques.</li> <li>Background in data engineering supporting model training and retrieval.</li> <li>Experience with Docker, Kubernetes, or large-scale microservice architectures.</li> <li>Experience applying ethical or responsible AI practices in enterprise contexts.</li> </ul> <p>&nbsp;</p> <p>Why Join Us?</p> <ul> <li>Shape an industry-leading AI and DaaS platform powering the next generation of cybersecurity insights.</li> <li>Lead the architecture of agentic systems used by both internal teams and Fortune-class clients.</li> <li>Work with a highly skilled, collaborative team building forward-looking AI products.</li> <li>Competitive compensation, benefits, and opportunities for growth.</li> </ul>