Babel Street is the trusted technology partner for the world’s most advanced identity intelligence and risk operations. We deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage. The actionable insights we deliver safeguard lives and protect critical assets around the world. Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K. For more information, visit www.babelstreet.com.
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.
You will work closely with the President & Chief AI Officer, as well as Product and Engineering leadership to execute the company’s AI strategy—balancing innovation with rigor, speed with safety, and capability with cost discipline. This role requires strong technical depth, hands-on experience, architectural judgment, and the ability to translate rapidly evolving AI technologies into reliable, customer-facing intelligence capabilities. You will lead teams building multilingual and multi-modal LLM and SLM pipelines, retrieval, agent-driven workflow systems, and graph-integrated reasoning capabilities that directly support intelligence applications—powering investigative, analytical, and operational workflows across Babel Street’s product suite.
You will focus on capabilities that automate analysis, reduce cognitive load, and power Babel Street’s future Knowledge Graph. A defining aspect of this role is ensuring all AI capabilities are delivered with strong guardrails, low hallucination rates, transparent behavior, and a relentless focus on winning on AI economics.
This is a hybrid role to be based out of either our Reston, VA or Somerville MA office.
ROLE SPAN
This role spans three integrated domains:
Generative AI & LLM/SLM Platform
You will help 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 to maximize accuracy, explainability, and mission impact. You will shape tooling and vendor decisions, lead model-provider partnerships, and architect scalable multilingual inference pipelines optimized through quantization, caching, routing, and GPU efficiency to ensure we consistently win on AI economics. You will 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
You will 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. In parallel, you will collaborate with Engineering teams to introduce agentic capabilities that improve engineering velocity, automate internal workflows, enhance data quality, and streamline operations. You will 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
You will collaborate with Product and Engineering to embed AI-native practices into the product suite and support the integration of AI capabilities into user-facing workflows. In this role, you will help productionize AI features through governance, telemetry, automated evaluation, adversarial testing, and responsible AI frameworks. You will contribute to the design and implementation of safeguards, guardrails, and hallucination-mitigation techniques, and support controls that monitor drift, enforce safe model behavior, and maintain transparency across the AI lifecycle—ensuring AI capabilities are measurable, trustworthy, and aligned with emerging regulatory expectations.
Across all domains, you will help build a high-performing AI organization and foster a culture defined by velocity, craftsmanship, safety, experimentation, and outcome-driven execution.
KEY RESPONSIBILITIES
Generative AI & LLM/SLM Platform
Agentic AI & Workflow Automation
AI Integration & Safe, Secure Delivery
Organizational Leadership & Collaboration
QUALIFICATIONS
EDUCATION
Bachelor’s degree in Computer Science, Engineering, AI/ML, or a related technical field required.
Master’s degree or PhD preferred.
Benefits at Babel Street (just to name a few...)
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.