Sr. Director, Generative & Agentic AI

Hatch IT • Somerville, MA

1d • Hybrid

About The Position

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 their 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 their Reston, VA or Somerville MA office.

Requirements

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

Nice To Haves

• Experience operating in regulated, high-stakes, or mission-critical environments is strongly preferred.
• Master’s degree or PhD preferred.

Responsibilities

• 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.
• 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.
• 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.
• 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.
• 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.
• Productionize AI features through governance, telemetry, automated evaluation, adversarial testing, and responsible AI frameworks.
• 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.
• Help build a high-performing AI organization and foster a culture defined by velocity, craftsmanship, safety, experimentation, and outcome-driven execution.
• 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.
• 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.
• 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.
• Lead and develop AI engineers and applied scientists through mentorship and technical leadership.
• Partner closely with Engineering, Product, and Data leaders to ensure aligned execution.
• Represent AI capabilities and strategy internally and, as needed, with customers and partners.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior