Sr. Director, Generative & Agentic AI

Role Summary

As Senior Director of Generative & Agentic AI, you will play a central role in Babel Street’s transformation into an AI-native risk intelligence organization. You will architect, operationalize, and scale generative and agentic AI capabilities across the Babel Street platform, ensuring they are mission-ready, safe, economically efficient, and deeply integrated with our products and data ecosystem.

Role Span

• Generative AI & LLM/SLM Platform

• Define and execute Babel Street’s generative AI strategy, establishing clear frameworks for when to deploy multilingual and multi-modal LLMs versus SLMs and when to apply RAG versus fine-tuning.
• Lead model tooling selection and partnerships across proprietary and open-weight ecosystems.
• Architect scalable, multilingual inference pipelines optimized for performance, reliability, and AI economics.
• Integrate embeddings and retrieval systems, develop evaluation and red-teaming pipelines, and ensure all generative capabilities meet mission-grade requirements for reliability, transparency, cost efficiency, and global language coverage.

• Agentic AI & Workflow Automation

• Design and implement agent architectures that deliver mission-aligned automation directly to customers, accelerating investigations, reducing cognitive load, and enabling intelligence applications and cross-product task execution through LLM- and agent-powered Knowledge Graph intelligence.
• Collaborate with Engineering teams to introduce agentic capabilities that improve engineering velocity, automate internal workflows, enhance data quality, and streamline operations.
• Operationalize agentic SDLC practices, build evaluation and guardrail systems, and establish observability frameworks to ensure reliable, secure, and transparent agent behavior, with a strong emphasis on cost-efficient execution and orchestration.

• AI Integration & Safe, Secure Delivery

• Support Product and Engineering teams in embedding AI capabilities into customer workflows.
• Contribute to AI productization through governance, telemetry, automated testing, and adversarial evaluation.
• Help design and implement safeguards, guardrails, and drift-monitoring controls.

Key Responsibilities

• Generative AI & LLM/SLM Platform

• Execute the generative AI strategy, including LLM vs. SLM and RAG vs. fine-tuning decision frameworks.
• Architect scalable, multilingual inference pipelines optimized for performance, reliability, and AI economics.
• Lead model tooling selection and partnerships across proprietary and open-weight ecosystems.

• Agentic AI & Workflow Automation

• Design agent architectures that automate investigations and cross-platform analytical workflows.
• Build agentic systems that leverage the Knowledge Graph for reasoning, task planning, and orchestration.
• Introduce agentic capabilities that improve internal engineering and operational workflows.

• AI Integration & Safe, Secure Delivery

• Support Product and Engineering teams in embedding AI capabilities into customer workflows.
• Contribute to AI productization through governance, telemetry, automated testing, and adversarial evaluation.
• Help design and implement safeguards, guardrails, and drift-monitoring controls.

Qualifications

• 10+ years of experience in AI/ML, applied analytics, or advanced data systems, including 3–5 years leading technical teams delivering production GenAI capabilities.
• Demonstrated experience applying generative and agentic AI capabilities to intelligence applications, including investigative analysis, entity and relationship discovery, pattern detection, and analyst-driven workflows in high-stakes or mission-critical environments.
• Strong technical expertise in agentic AI, workflow automation, orchestration frameworks, and evaluation techniques.
• Experience designing systems that minimize hallucinations and enforce safe, predictable AI behavior.
• Hands-on experience with cloud-native AI infrastructure, inference optimization, and cost-aware system design.
• Ability to translate complex AI concepts into practical, mission-ready product capabilities.
• Strong communication skills and the ability to collaborate effectively across technical and non-technical teams.
• Experience operating in regulated, high-stakes, or mission-critical environments is strongly preferred.

Education

• Bachelor’s degree in Computer Science, Engineering, AI/ML, or a related technical field required.
• Master’s degree or PhD preferred.

Benefits

• Health Benefits: Babel Street covers 85-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances – for you and your family!
• Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match.
• Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives.
• Holidays: Babel Street provides employees with 12 paid Federal Holidays
• Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education.

Company Information

• Babel Street is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Further, Babel Street will not discriminate against applicants for inquiring about, discussing or disclosing their pay or, in certain circumstances, the pay of their co-worker, Pay Transparency Nondiscrimination.
• In addition, Babel Street's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request, we will provide you with more information about such accommodations.
• Risk Disclosure: Babel Street does not guarantee the accuracy of the salary range provided above. Salary will be determined based on factors such as location, experience, and qualifications.