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Ai Director Jobs in Reston, VA (NOW HIRING)

Director, Business Development

Reston, VA ยท On-site

$120 - $180/hr

Empower AI gives federal agency leaders the tools to elevate the potential of their workforce with a direct path for meaningful transformation. Headquartered in Reston, Va., Empower AI leverages ...

The Assistant Director must possess deep, hands-on technical fluency to command respect from engineering teams and validate architectural decisions. * Core AI/ML: Expert-level understanding of Deep ...

The Assistant Director must possess deep, hands-on technical fluency to command respect from engineering teams and validate architectural decisions. * Core AI/ML: Expert-level understanding of Deep ...

The Assistant Director must possess deep, hands-on technical fluency to command respect from engineering teams and validate architectural decisions. * Core AI/ML: Expert-level understanding of Deep ...

Showing results 21-40

Ai Director information

How much does an AI director make?

An AI director's salary typically ranges from $120,000 to $200,000 annually, depending on experience, industry, and location. Senior roles or those in large tech companies can earn higher compensation, often including bonuses and stock options. Strong leadership, technical expertise, and knowledge of AI tools are important for this role.

What does an AI Director do?

An AI Director oversees the development and implementation of artificial intelligence strategies within an organization or project. Their responsibilities include managing AI teams, setting project goals, ensuring ethical AI practices, and integrating AI technologies to meet business objectives. They often collaborate with data scientists, engineers, and other stakeholders to drive innovation and solve complex problems using AI solutions.

How to become an AI director?

To become an AI director, candidates typically need a strong background in computer science, machine learning, or data science, often holding a master's or doctoral degree. Relevant experience in AI development, leadership skills, and familiarity with AI tools and frameworks are essential, along with a proven track record of managing AI projects and teams.

What are the key skills and qualifications needed to thrive as an AI Director?

To thrive as an AI Director, you need deep expertise in artificial intelligence, machine learning, and data science, typically supported by an advanced degree in computer science or related fields. Familiarity with AI frameworks (like TensorFlow or PyTorch), cloud platforms, and experience managing large-scale AI projects are crucial, as are certifications in relevant technologies. Strong leadership, strategic thinking, and communication skills help drive cross-functional teams and align AI initiatives with business objectives. These abilities ensure the successful development, deployment, and adoption of AI solutions that deliver real business value.

How does an AI Director typically collaborate with cross-functional teams in an organization?

An AI Director works closely with various departments such as engineering, product management, data science, and executive leadership to align AI initiatives with business goals. Collaboration often involves leading strategy sessions, setting project priorities, and ensuring technical teams have the resources and guidance needed to deliver on objectives. Effective communication is key, as the AI Director must translate complex technical concepts into business value and coordinate efforts across multiple stakeholders. Regular meetings and progress reviews help maintain alignment and address challenges proactively.

What is the difference between Ai Director vs Data Scientist?

AspectAi DirectorData Scientist
Required CredentialsAdvanced degrees in AI, computer science, or related fields; leadership experienceBachelor's or master's in data science, statistics, or related fields; strong programming skills
Work EnvironmentOversees AI projects, manages teams, collaborates with executivesAnalyzes data, builds models, reports findings, often works independently or in small teams
Employer & Industry UsageTech companies, AI startups, large enterprises implementing AI strategiesTech firms, finance, healthcare, research institutions

While both roles involve working with data and AI, the Ai Director focuses on strategic oversight, leadership, and managing AI initiatives, whereas the Data Scientist concentrates on data analysis, model development, and technical implementation.

What are the most commonly searched types of Ai jobs in Reston, VA? The most popular types of Ai jobs in Reston, VA are:
What cities near Reston, VA are hiring for Ai Director jobs? Cities near Reston, VA with the most Ai Director job openings:
Infographic showing various Ai Director job openings in Reston, VA as of August 2026, with employment types broken down into 71% Full Time, 25% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.

Sr. Director, Generative & Agentic AI

Hatch IT

Reston, VA โ€ข On-site

Full-time

Re-posted 17 days ago


Job description

hatch I.T. is partnering with Babel Street to find a Sr. Director, Generative & Agentic AI. Please see details below:
About the Role
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.
About the Company
Babel Street is the trusted technology partner for the world's most advanced identity intelligence and risk operations. They 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.
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.
What you will do:
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.

Organizational Leadership & Collaboration
  • 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 you will bring:
  • 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.

$210,000 - $240,000 a year
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.