ROLE SUMMARY 

Babel Street is building mission-ready intelligence applications that help analysts move from signal to insight faster, with higher trust. As the Director of Design Engineering, you will own the end-to-end product experience key workflows—designing intuitive interfaces and shipping production-grade front-end code that integrates AI directly into the user journey. 

This is a “builder” role: you will pair human-centered design with strong front-end engineering to deliver experiences that feel simple, fast, and trustworthy—even when the underlying systems (data fusion, entity resolution, AI agents, multimodal analytics) are complex. You’ll collaborate tightly with Product, Platform, and AI teams to operationalize AI in the UI with guardrails, transparency, and human-machine teaming. 

This is a hybrid role working out of either our Reston, VA or our Somerville, MA office

WHAT YOU’LL DO (KEY RESPONSIBILITIES) 

Own the AI-first user experience for intelligence workflows 

• Design and implement workflows where AI meaningfully reduces cognitive load (e.g., investigation setup, triage, summarization, entity linking, report generation, alert review). 

• Build “AI-in-the-flow” patterns: inline suggestions, copilots, agent task panels, explainable recommendations, smart defaults, and guided wizards—without turning the product into a chat box. 

• Define interaction patterns for agentic experiences (tasking, progress, tool calls, approvals, undo/redo, auditability, and fail-safe fallbacks). 

Human-Centered Design (HCD) with real users and real constraints 

• Conduct lightweight user research (interviews, usability tests, workflow observation) and translate insights into journey maps, task flows, wireframes, prototypes, and shipped UI. 

• Partner with Product to clarify user problems, success criteria, and tradeoffs—then execute quickly and iteratively. 

• Ensure the UX supports novice-to-expert progression (discoverability for new users, speed and power features for experts). 

Build and ship high-quality front-end software 

• Implement designs in a modern front-end stack (typically React + TypeScript), delivering clean, testable, accessible, performant UI. 

• Build reusable components and patterns; contribute to (or lead) a design system using tools like Figma + Storybook. 

• Instrument experiences with analytics/telemetry to measure adoption, workflow success, and time-to-insight improvements. 

Trust, safety, and transparency in AI experiences 

• Design for “evidence-first” outputs: citations, sources, confidence indicators, what-changed diffs, and clear user controls. 

• Implement guardrails in the UI: policy-aware interactions, redaction/PII-aware patterns (where applicable), and safe failure modes. 

• Close the loop with feedback: capture user ratings, corrections, and outcomes to improve models and workflows over time. 

Cross-functional execution and leadership 

• Work daily with Product, AI/ML, and Backend teams to define API contracts, data needs, latency targets, and UX acceptance criteria. 

• Raise the bar on craft: advocate for coherent UX, consistent patterns, and high-quality delivery—while keeping momentum and pragmatism. 

• Mentor others informally through design critiques, code reviews, and clear communication. 

WHAT YOU BRING (REQUIRED QUALIFICATIONS) 

• 10+ years of experience delivering UX/UI design + front-end engineering for modern web applications (or equivalent depth). 

• Strong portfolio demonstrating shipped product work (not just concepts)—including complex workflows and/or data-rich applications. 

• Proficiency building production UIs with React and TypeScript (or comparable modern framework experience). 

• Fluency in HCD methods: user interviews, task analysis, prototyping, usability testing, and iterative delivery. 

• Strong product instincts: can translate ambiguity into clear workflows, make smart tradeoffs, and ship in increments. 

• Experience integrating with APIs and data services; comfort collaborating on interface contracts and edge cases. 

• Working knowledge of accessibility (WCAG fundamentals), performance basics, and secure UI patterns (auth, RBAC-aware UX). 

Benefits at Babel Street (just to name a few...)

• 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.                 

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.

Role Summary

Babel Street is building an AI-native, agent-ready, API-first intelligence platform where computer vision, NLP, and document enrichment continuously produce signals about people, places, organizations, and events. The knowledge graph transforms those signals into a coherent, queryable representation of the world.

We are hiring a Knowledge Graph Engineer to help design, build, and operate the entity resolution and graph layer that connects our multimodal pipelines. You will work closely with the Director of Computer Vision and collaborate with ML, platform, and data engineering teams to connect mentions in text, objects in images, locations in geotagged media, and entities in structured sources into a unified graph.

This is a hands-on engineering role where you will contribute to production systems, grow your expertise in graph modeling and entity resolution, and help shape a platform that is still evolving. This will be a hybrid role based out of either our Reston, VA or Somerville, MA office.

Key Responsibilities

• Implement and evolve graph schemas and entity models for people, locations, organizations, images, and events
• Build and maintain entity resolution pipelines that reconcile entities across NLP outputs (GLiNER, spaCy), computer vision outputs (object detection, OCR, face recognition, geolocation), and structured data sources
• Develop ingestion pipelines that write resolved entities into graph systems such as ArangoDB and Spanner Graph or BigQuery Graph
• Contribute to cross-modal linkage between text, images, and geospatial data, including confidence scoring and provenance tracking
• Collaborate with computer vision engineers to integrate visual entity outputs into the graph layer
• Help build graph-backed APIs and services used by downstream products and workflows
• Write tests, contribute to design discussions, and support improvements to data quality and pipeline reliability

Why This Role Matters

The knowledge graph is where Babel Street’s signals become usable intelligence. A detected landmark, a name extracted from text, an organization mentioned online, and a face identified in an image all become more valuable when they resolve to a shared representation of an entity.

In this role, you will help:

• Connect multimodal signals into a unified graph
• Improve the accuracy and consistency of entity resolution
• Enable downstream search, analytics, and agent workflows

Required Qualifications

• 2–5 years of professional software engineering experience (or equivalent experience through internships and projects)
• Proficiency in Python and at least one typed language (Java, Go, C#, or TypeScript)
• Familiarity with at least one graph database or graph processing framework (ArangoDB, Neo4j, TigerGraph, JanusGraph, NetworkX, or similar)
• Solid understanding of SQL and core data modeling concepts (keys, normalization, joins, indexing)
• Ability to work across teams, incorporate feedback, and make steady progress in ambiguous problem spaces

Preferred Qualifications

• Exposure to entity resolution, record linkage, or deduplication
• Familiarity with semantic modeling or schema design (RDF, OWL, property graphs, JSON-LD)
• Experience with cloud platforms such as GCP (Spanner, BigQuery, Cloud Run)
• Interest in computer vision, NLP, geospatial data, or multimodal systems
• Experience testing data pipelines, implementing data quality checks, or working with observability tools
• Exposure to search, ranking, or retrieval-based systems

What Success Looks Like (First Six Months)

• Month 1–2: Ramp up on the graph stack, contribute to existing pipelines, and ship initial changes
• Month 3–4: Take ownership of a component or pipeline with guidance, including testing and documentation
• Month 5–6: Deliver improvements to entity resolution quality, graph ingestion, or cross-modal linkage, and contribute to design discussions

Benefits at Babel Street (just to name a few...)

• 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.                 

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.

ROLE SUMMARY 

As Head of Data you will define and lead Babel Street’s North Star Data Strategy and Architecture, building a cohesive, scalable, and AI-native data platform that transforms fragmented systems into a unified foundation for intelligence, analytics, and product innovation. 

You will own the full lifecycle of data across the organization, from ingestion and storage to semantics, retrieval, and productization. Your mandate is to unify fragmented systems into a cohesive, scalable, and AI-ready data platform that directly enables investigative, analytical, and operational workflows across Babel Street’s product suite. 

You will work closely with Product and Engineering leadership, to ensure that data is not just infrastructure, but a core competitive advantage. This includes powering Babel Street’s Knowledge Graph, enabling agentic and generative AI systems, and delivering data capabilities that are reliable, performant, and economically efficient at scale. 

This role requires deep technical expertise, strong architectural judgment, and the ability to translate complex data challenges into customer-impacting intelligence capabilities. 

This hybrid role will be based in our Reston, VA or Somerville, MA office. 

ROLE SPAN 

This role spans four integrated domains: 

1. Data Platform & Storage Architecture 

You will help define and evolve Babel Street’s unified data platform, consolidating warehouse, search and object storage systems into a cohesive scalable foundation. This includes establishing clear patterns for when and how to use analytical warehouses, search/index systems, and object storage to support diverse workloads across the business. 

You will architect systems that operate at petabyte scale, ensuring high performance, reliability, and flexibility across batch and real-time data. A key focus will be driving platform rationalization while maintaining continuity of operations and minimizing risk. 

You will also establish standards for data ingestion, transformation, and lifecycle management, ensuring consistency and efficiency across the platform.  

2. Data Semantics, Knowledge Graph & Identity 

You will own the semantic foundation of Babel Street’s data ecosystem, defining how data is modeled, connected, and understood across products and systems.  

This includes building and evolving the company's knowledge graph, including entity resolution, identity modeling, and relationship mapping across disparate data sources. You will establish ontology and schema strategies that ensure consistent interpretation of data across teams, products, and AI systems. 

Your work will enable graph-integrated reasoning and provide the structures context required for intelligence workflows and AI-driven applications. 

3. Data Access, Retrieval & AI-Enablement 

You will design and operate data access patterns that power both human and machine consumption of data, including API’s, query layers and retrieval systems.  

This includes enabling hybrid retrieval approaches across structured, unstructured and vector-based data to support LLMs, RAG pipelines, and agentic systems. You will ensure that data is accessible in a way that is performant, scalable, and optimized for AI workloads. 

You will partner closely with AI and Applied ML teams to ensure seamless integration between data systems and model-driven capabilities, enabling reliable, explainable, and efficient intelligence generation. 

4. Data Productization, Governance & Economics 

You will establish a data-as-a-product operating model, ensuring that data assets are discoverable, reusable, and governed with clear ownership and accountability.  

This includes defining contracts, enforcing quality standards, and implementing metadata and governance frameworks that scale across the organization. 

You will also own the economics of the data platform, ensure efficient use of storage and compute, and optimize cost per query, cost per workload, and overall system efficiency. A key focus will be enabling scalable AI usage through efficient data retrieval and storage strategies. 

KEY RESPONSIBILITIES 

Define the North Star Data Architecture 

• Establish and evolve the target-state data architecture, aligning storage, compute, search, and access patterns into a unified platform
• Drive architectural clarity across warehouse, search, object storage, and real-time systems
• Ensure consistency in schemas, metadata, and governance frameworks across all data domains 

Build an AI-Native Data Foundation 

• Design a data platform optimized for AI and agentic workloads, including: 
  API-first, agent-callable data services
• Hybrid retrieval patterns (search + analytical + vector)
• Real-time and batch data unification
• Enable scalable support for LLMs, RAG pipelines, and intelligence workflows 

Own Data as a Product 

• Establish a data-as-a-product operating model, enabling discoverable, reusable, and well-governed data assets
• Define and standardize data contracts, ownership models, and domain boundaries
• Translate platform capabilities into customer-facing data products and differentiators 

Lead Platform Rationalization and Evolution 

• Rationalize and evolve the current ecosystem (e.g., BigQuery, Elasticsearch/OpenSearch, S3) into a cohesive and cost-efficient architecture
• Lead phased, low-risk migrations and consolidations aligned to business priorities
• Balance short-term pragmatism with long-term architectural integrity 

Own Performance, Reliability, and Cost Economics 

• Accountable for performance, scalability, and reliability of all data systems
• Establish clear unit economics for data (e.g., cost per query, cost per workload, storage efficiency)
• Implement strong observability, SLOs, and incident management practices 

Required Qualifications: 

• 10+ years of experience in data platforms, data engineering, or distributed systems
• Strong background working within multi-cloud or hybrid environments, including hands-on experience with Google Cloud Platform (GCP)
• Proven experience designing and evolving large-scale data platforms through major architectural transitions (e.g., warehouse, search, Lakehouse, or multi-cloud transformations)
• Deep expertise across multiple data paradigms, including:
• Analytical warehouses
• Search/index systems
• Object storage and distributed data systems
• Experience building platforms that support AI, ML, or agent-driven systems
• Familiarity with vector search, retrieval architectures, and modern AI data patterns
• Experience with graph-based data models, entity resolution, or knowledge graphs
• 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, or a related technical field required. 
Master’s degree or PhD preferred. 

Benefits at Babel Street (just to name a few...)

• 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.                 

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.

Role Summary 

We are seeking a Principal Engineer to lead Babel Street’s API and MCP platform strategy and delivery as we evolve toward an AI-native, agent-driven platform. 

This is a hands-on, senior technical leadership role responsible for defining and delivering API-first platform capabilities that enable both developers and AI agents to interact with Babel Street’s services. You will lead the design and implementation of semantic APIs, Model Context Protocol (MCP) integrations, and context-aware service patterns that power next-generation intelligence workflows. 

This role requires a finger-on-keyboard engineer who can both define direction and deliver foundational systems. You will partner closely with AI, Data, and Platform teams to ensure Babel Street’s APIs and services are consistent, discoverable, scalable, and optimized for agentic workflows. 

You will work in close partnership with the Architecture function to align on long-term technical direction, ensuring API and MCP platform decisions are consistent with the company’s broader architectural vision while maintaining a strong focus on execution and delivery. 

This is a hybrid role working out of either our Reston, VA or Somerville, MA office. Full remote may be considered.

Why This Role Matters 

This role will be instrumental to Babel Street’s AI-native technology strategy. The API and MCP platform will serve as the interface layer between data, AI, and product capabilities, enabling agents, developers, and systems to interact seamlessly. 

This is a high-impact, senior technical leadership role with broad influence across the organization and the opportunity to shape the future of Babel Street’s platform.  The position spans four core domains: 

API Platform & Strategy 

You will define and lead Babel Street’s API-first platform strategy, establishing consistent patterns for service design, versioning, discoverability, and governance. 

You will help evolve the platform toward agent-ready APIs, ensuring services are consumable by both human developers and AI agents. You will establish standards for API consistency, reliability, and performance across the organization. 

You will also work closely with product and engineering teams to ensure APIs are designed as first-class platform capabilities, not just service interfaces. 

MCP & Agent Integration 

You will lead Babel Street’s Model Context Protocol (MCP) strategy and implementation, enabling agents and AI systems to interact with services in a standardized and scalable way. This includes defining patterns for: 

• MCP service exposure 
• Tool and service discovery  
• Agent-to-service communication  
• Context-aware interactions  

You will partner closely with AI and platform teams to enable agent-native workflows across the organization. 

Semantic APIs & Agent-Ready Interfaces 

You will lead the design of semantic, agent-friendly APIs, where documentation becomes a first-class interface for AI-driven systems. This includes defining standards for: 

• API descriptions optimized for agents 
• Schema consistency and semantic modeling  
• Tool and service discoverability  
• API documentation optimized for agent consumption  

You will establish best practices for documentation-as-code, ensuring APIs are designed for both developers and AI systems. 

Context Management & Runtime Patterns 

You will define patterns for context-aware APIs and services, including: 

• Context management and retrieval 
• Context caching  
• Session and state management  
• Memory-aware service interactions  

You will help design scalable context-aware systems leveraging technologies such as Vertex AI Context Caching and related frameworks. 

Key Responsibilities 

• Partner closely with Architecture to define and lead Babel Street’s API and MCP platform strategy 
• Design and deliver semantic, agent-ready APIs  
• Establish MCP standards and implementation patterns  
• Define context management patterns for agent workflows  
• Partner with AI and Data teams to enable agent-native architectures  
• Establish API governance and platform standards  
• Build foundational frameworks and reusable components  
• Provide hands-on technical leadership and mentorship  
• Partner with Google and other vendors on platform capabilities  
• Drive adoption of API and MCP standards across engineering teams  

Required Qualifications 

• 10+ years of software engineering experience 
• Experience operating at Principal Engineer or Staff+ level 
• Strong hands-on experience building distributed systems  
• Experience designing and building API-first platforms 
• Experience with cloud-native architectures (GCP preferred)  
• Experience building developer platforms or service-oriented architectures  
• Strong system design and architectural thinking skills 
• Proven ability to lead cross-team technical initiatives  

Preferred Qualifications 

• Hands-on work with Google Cloud Platform (GCP) 
• Familiarity with Vertex AI Agent Engine  
• Background in ADK and reasoning frameworks such as LangChain 
• Understanding of the Model Context Protocol (MCP)  
• Exposure to data warehouse technologies like BigQuery and Snowflake 
• Knowledge of Apigee or similar API gateway solutions  
• Proven ability to design semantic APIs for AI or agent-driven use cases  
• Experience managing context or building memory systems  
• Development of agent-based architectures or orchestration frameworks  
• Exposure to Anti-Gravity 

What Success Looks Like 

30 Days 

• Assess current API and platform architecture 
• Define API and MCP platform strategy  
• Identify early opportunities for standardization  

60 Days 

• Deliver initial platform frameworks and standards 
• Begin rollout of semantic API patterns  
• Establish MCP integration approach  

90 Days 

• Agent-ready APIs in production 
• MCP-enabled services deployed
• Clear platform standards adopted across teams
• Measurable improvement in API consistency and developer velocity  

Benefits at Babel Street (just to name a few...)

• 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.                 

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.

ROLE SUMMARY 

As an Engineer on the Generative & Agentic AI team, you will play a hands-on role in building, deploying, and operating AI capabilities that power Babel Street’s intelligence applications. You will work closely with senior AI leaders, product teams, and engineers to implement generative and agentic AI solutions that support investigative, analytical, and operational workflows across the platform. 

This is an execution-focused role for an engineer with strong foundations in machine learning and generative AI who is excited to work on real-world, mission-driven applications. You will contribute directly to LLM and SLM pipelines, retrieval and grounding systems, agent workflows, and AI-enabled features—while learning how to deliver AI that is safe, reliable, cost-efficient, and production-ready. 

This is a hybrid role to be based out of either our Reston, VA/Washington DC office or our Somerville MA office.

ROLE FOCUS 

This role spans three practical execution areas: 

Generative AI & Model Development 

You will help implement and operate LLM- and SLM-based systems, contributing to prompt development, fine-tuning, evaluation, and inference optimization. You will support retrieval-augmented generation (RAG) pipelines, embeddings, and grounding techniques to ensure AI outputs are accurate, explainable, and aligned with intelligence use cases. 

Agentic AI & Workflow Automation 

You will assist in building and integrating agent-based workflows that automate analytical tasks, connect platform services, and support intelligence applications. This includes implementing agent logic, tool-use patterns, and basic orchestration under the guidance of senior engineers. 

AI Engineering & Production Delivery 

You will help productionize AI capabilities using modern AI SDLC tools and practices, contributing to evaluation, testing, telemetry, and guardrails that reduce hallucinations and ensure safe behavior. You will work within established governance frameworks to ensure AI features are measurable, reliable, and cost-aware. 

KEY RESPONSIBILITIES 

• Implement and maintain LLM and SLM pipelines, including prompt engineering, inference, and evaluation. 

• Support RAG pipelines, embeddings, and retrieval systems used in intelligence applications. 

• Assist in building agent workflows that automate analytical or operational tasks. 

• Write clean, maintainable code (Python or others) to support AI services and integrations. 

• Contribute to AI evaluation, testing, and hallucination-mitigation techniques. 

• Use AI-assisted development tools (e.g., Copilot, Cursor) to improve development velocity and quality. 

• Collaborate with Product and Engineering teams to integrate AI capabilities into user-facing workflows. 

• Follow established AI governance, safety, and cost-optimization practices. 

QUALIFICATIONS 

Required 

• 5+ years of experience in software engineering, machine learning, or applied AI roles. 

• Hands-on experience working with LLMs and/or SLMs, including prompting, inference, or fine-tuning. 

• Experience building or contributing to RAG pipelines, embeddings, or retrieval systems. 

• Familiarity with agent-based systems or workflow automation (academic, professional, or open-source). 

• Strong programming skills in Python; experience with common libraries (PyTorch, TensorFlow, etc.). 

• Solid foundation in machine learning concepts (training, evaluation, overfitting, metrics). 

• Experience using or contributing to modern AI/ML tooling and workflows (ML pipelines, evaluation scripts, model serving). 

• Ability to work in a collaborative, fast-moving, mission-driven environment. 

Preferred 

• Experience applying AI to intelligence, investigative, analytical, or risk-related applications. 

• Familiarity with vector databases, graph databases, or knowledge graphs. 

EDUCATION 

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field required. 
Advanced degree is a plus but not required. 

Benefits at Babel Street (just to name a few...)

• 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.                 

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.

ROLE SUMMARY 

As the Senior Architect of AI Governance & Risk, you will lead the design and operationalization of Babel Street’s AI trust framework across safety, privacy, security, bias/fairness, and transparency. You will ensure our AI-enabled products—spanning LLM-powered workflows, agentic systems, and multimodal capabilities—are built and deployed with measurable controls, defensible documentation, and audit-ready evidence. 

A core part of this role is to create, institutionalize, and operationalize Babel Street AI Principles—and translate them into the policies, engineering standards, delivery gates, customer assurances, and reporting artifacts that guide how we build and deploy AI across the company. 

This role requires extensive partnership with Product, Engineering, Security (CISO), Legal/Privacy, and Customer Success teams. You will serve as the connective tissue between these functions, ensuring governance requirements are understood, adopted, and embedded into the AI lifecycle—from design through production monitoring and incident response.  

The ideal candidate is execution-oriented with a focus on customer-facing outcomes. You will translate emerging AI policy and customer requirements into concrete engineering controls and reusable collateral that accelerates RFI/RFP responses, supports due diligence, and reduces risk without slowing product velocity.  

ROLE FOCUS 

This role spans three practical execution areas: 

AI Principles & Governance Architecture 

You will define Babel Street’s AI Principles and build the governance operating system that turns principles into action—standards, controls, documentation, and release gates that are implementable by engineering teams and measurable in production. 

AI Policy Intelligence, RFI/RFP Enablement & Reporting Collateral 

You will track and interpret emerging AI policy, regulations, and standards and assess their impact on Babel Street’s products and business. You will translate these requirements into roadmap implications, compliance strategies, and customer-ready collateral—enabling fast, consistent responses to RFIs/RFPs, security questionnaires, audits, and due diligence requests. 

Responsible AI Assurance Across Safety, Privacy, Security, Bias/Fairness & Transparency 

You will own the assurance posture for Babel Street AI— partnering with Engineering, Security, Legal/Privacy, and Product teams to ensure safety metrics, privacy controls, AI security testing, bias/fairness evaluation practices, and transparency artifacts (model/system cards) are defined, implemented, measured, and maintained over time. 

KEY RESPONSIBILITIES 

AI Strategy, Policy Intelligence & Business Impact 

• Create and operationalize Babel Street’s AI principles into enforceable engineering and product standards (e.g., secure-by-design patterns, privacy boundaries, oversight requirements, transparency expectations). 

• Monitor emerging AI policy, regulatory, and standards developments relevant to Babel Street markets and customer segments. 

• Partner with leadership to chart a pragmatic AI compliance and assurance strategy that supports growth and reduces friction in procurement cycles. 

AI Governance Program Design & Framework Development 

• Define and maintain Babel Street’s AI governance framework by embedding  AI principles into delivery workflows across the development lifecycle.   

• Partner with Engineering to maintain an AI model/system inventory, including third-party AI providers (e.g., GPT-4, Gemini, Claude), integrations, data touchpoints, and output constraints. 

• Define documentation standards for traceability: model lineage, evaluation results, monitoring plans, limitations, and intended/prohibited use. 

Customer Assurance: RFI/RFP Response, Due Diligence & Reporting 

• Ensure Babel Street AI Principles are reflected consistently in customer-facing commitments, product documentation, training materials, and reporting artifacts. 

• Lead the company’s responsible AI posture in AI-focused RFI/RFP responses, audit support, and customer due diligence—ensuring responses are consistent, evidence-backed, and defensible. 

• Create a repeatable evidence program (what we collect, how we maintain it, and how we produce it quickly and consistently). 

Safety & Reliability (Partner: Engineering, Product) 

• Partner with Engineering to define safety metrics (reliability, robustness, response times, bias correction, etc..) and ensure these are tracked and measured in production 

• Coordinate with Product to establish policies and procedures for AI safety, including documented response times for system failures 

• Lead the development of AI-specific Incident Response Procedures (IRPs) in partnership with Security and Engineering teams, ensuring readiness to address AI safety-related issues 

Privacy & Data Handling (Partner: Legal/Privacy, Engineering) 

• Partner with Legal/Privacy to define and enforce AI privacy requirements including data minimization, retention boundaries, and third-party data protection 

• Coordinate customer data usage positions: whether customer data is used for AI model training/improvement, and ensure opt-out mechanisms are clearly documented and enforceable 

• Lead privacy risk assessments for AI features and ensure data handling practices with third-party AI providers are documented and compliant (CCPA, ISO 42001, relevant regulations) 

Security & Audit (Partner: Security/CISO, Engineering) 

• Partner with Security (CISO) to establish AI security requirements, including access controls and employee/third-party access management to customer data 

• Coordinate internal and external AI security audits that address AI-specific vulnerabilities (prompt injection, jailbreaking, etc.) with clear remediation processes 

• Ensure output validation processes are in place to identify risks of unreliable or harmful content 

QUALIFICATIONS 

Required 

• 8+ years of experience across governance, risk, security, privacy, compliance, or systems architecture, including 3+ years supporting AI/ML-enabled systems in production. 

• Demonstrated ability to translate governance requirements into implementable controls and engineering practices (not policy-only work). 

• Strong understanding of AI governance frameworks and standards (e.g., NIST AI RMF, ISO/IEC 42001, ISO/IEC 23894) and ability to translate requirements into organizational processes 

• Experience producing customer-facing and audit-ready content: RFI/RFP responses, control narratives, assurance artifacts, and executive-ready summaries 

• Strong stakeholder management and influence skills; able to drive decisions, build consensus, and maintain accountability across multiple teams 

• Excellent written and verbal communication skills; able to craft clear, defensible positions for customers, executives, and internal teams 

EDUCATION 

Bachelor’s degree  or equivalent experience in Computer Science, Engineering, Information Assurance, Data Science, Public Policy (with technical depth), or a related field required. 
Advanced degree or certifications in governance, risk, privacy, or AI policy is a plus but not required. 

Benefits at Babel Street (just to name a few...)

• 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.                 

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.

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

• 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. 

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 at Babel Street (just to name a few...)

• 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.                 

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.

ROLE SUMMARY:

As an Engineer on the Image & Computer Vision AI team, you will play a hands-on role in developing and deploying computer vision capabilities that support Babel Street’s intelligence applications. You will build systems that extract, analyze, and reason over visual data—enabling facial matching, object and scene understanding, geolocation and location inference from imagery, and multimodal intelligence workflows. 

This role is execution-focused and suited for engineers with strong foundations in computer vision, image processing, and machine learning who want to apply their skills to real-world, mission-driven problems. You will work closely with AI, Product, and Engineering teams to deliver reliable, scalable, and cost-efficient vision capabilities, including integration with multimodal LLM systems that allow users to search and reason over images using natural language. 

This is a hybrid role to be based out of either our Reston, VA/Washington DC office or our Somerville MA office.

ROLE FOCUS;

This role spans three practical execution areas: 

Computer Vision & Image Analytics 

You will implement and operate image analytics pipelines that support facial matching, object detection, scene understanding, and image similarity. This includes image preprocessing, feature extraction, model inference, evaluation, and performance optimization to meet mission-grade accuracy and latency requirements. 

Geospatial & Location Inference from Imagery 

You will contribute to capabilities that infer location, context, or environmental attributes from imagery—leveraging visual cues, metadata, and learned representations. This includes supporting image-based geolocation, landmark recognition, and contextual scene analysis used in intelligence workflows. 

Multi-Modal AI & Image Search 

You will support multimodal AI systems that combine vision models with LLMs, embeddings, and retrieval pipelines to enable natural-language search and reasoning over images and image collections. You will help integrate visual understanding into broader intelligence applications and workflows. 

KEY RESPONSIBILITIES:

• Build and maintain computer vision pipelines for image ingestion, preprocessing, inference, and evaluation. 

• Implement facial matching, and identity-related vision workflows in accordance with accuracy, safety, and compliance requirements. 

• Develop and support object detection, image similarity, and scene understanding models. 

• Contribute to image-based geolocation and location inference capabilities using visual features and contextual signals. 

• Support multimodal AI workflows that combine image embeddings with LLM-based search and reasoning. 

• Write clean, maintainable Python code and contribute to production services and APIs. 

• Assist with model evaluation, bias testing, and accuracy monitoring for vision systems. 

• Optimize inference pipelines for performance, scalability, and cost efficiency (GPU usage, batching, model selection). 

• Collaborate with Product and Engineering teams to integrate vision capabilities into user-facing intelligence applications. 

QUALIFICATIONS: 

Required 

• 3+ years of experience in computer vision, image processing, or applied machine learning. 

• Hands-on experience with computer vision models and techniques (e.g., CNNs, transformers for vision, feature embeddings). 

• Experience building or integrating image analytics such as facial recognition, object detection, or image similarity. 

• Strong programming skills in Python; experience with common CV/ML libraries (PyTorch, TensorFlow, OpenCV, etc.). 

• Solid understanding of machine learning fundamentals, model evaluation, and performance tradeoffs. 

• Experience working with large image datasets and production ML pipelines. 

• Ability to work collaboratively in a fast-moving, mission-driven engineering environment. 

Preferred 

• Experience with facial matching or biometric systems in regulated or high-stakes environments.
• Experience with image-based geolocation or scene/location inference.
• Familiarity with multimodal AI systems, including combining vision models with LLMs or natural-language search. 

EDUCATION:

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field required. 
Advanced degree is a plus but not required. 

Benefits at Babel Street (just to name a few...)

• 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.                 

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.