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We are looking for an experienced, opinionated, and highly technical Staff Data Engineer to define the long-term direction of our Data Platform.
This role is ideal for a senior data leader who combines deep hands-on expertise with strong architectural judgment, enjoys mentoring others, and takes full ownership of complex, high-scale data systems.
You will drive platform architecture, set engineering standards, and lead the design and delivery of scalable batch and streaming data solutions on AWS.
Key Responsibilities:
Technical Leadership & Architecture:
Own and evolve the overall data platform architecture-scalability, reliability, security, and maintainability.
Lead the long-term strategic direction of the platform, balancing performance, cost, and operational excellence.
Introduce and drive adoption of modern data paradigms: lakehouse (Iceberg), event-driven pipelines, schema-aware processing.
Data Lake & Architecture Ownership:
Design, model, and evolve the Data Lake architecture, including:
Storage layout and data organization
Data formats and table design (e.g., Iceberg)
Batch and streaming ingestion patterns
Schema governance and lifecycle policies
Define and promote best practices for data modeling, partitioning, and data quality.
Ensure the Data Lake supports analytics, ML workloads, and operational systems at scale.
Platform Engineering:
Design and build high-scale ETL/ELT pipelines leveraging Apache Spark (EMR/Glue) and AWS-native services.
Optimize production-grade pipelines using S3, Athena, Kinesis, Lambda, Step Functions, and EKS.
Lead the rollout of modern patterns such as lakehouse architectures and event-driven data pipelines.
Security & Governance:
Ensure alignment with AWS security best practices-IAM, encryption, auditing, and compliance frameworks.
Partner with security and governance teams to support regulated and sensitive data environments.
Mentorship & Collaboration:
Serve as a technical mentor to data engineers; elevate team capabilities.
Lead architecture reviews and cross-team design discussions.
Work closely with Data Science, ML Engineering, Backend, and Product teams to deliver end‑to‑end data solutions.

We are looking for an experienced and visionary Staff Data Architect to play a critical role in defining and shaping the data architecture for our flagship investigative analytics platform. In this position, you will design and guide the implementation of robust, scalable, and secure data pipelines that power advanced data processing for AI-driven insights as part of digital investigations.
You will work closely with cross-functional teams to drive technology alignment and ensure architectural excellence across multiple domains. This is a high-impact role, ideal for someone with deep technical expertise and strong strategic thinking, who thrives in a dynamic, collaborative environment and is passionate about building world-class technology platforms.
As our Data Architect, you will own the vision for how we manage, move, and leverage data within our SaaS product suite. Your role is pivotal in designing and implementing a robust data architecture that supports both real-time operational needs and advanced analytics, all within a scalable and cost-effective cloud-native environment.
Responsibilities:
Own the Data Vision: Take ownership of the data architecture, including our data lake, data warehouse, and ETL/ELT pipelines, to support our product teams and business intelligence.
Cost Optimization & Scalability: Provide architectural leadership and guidance to ensure our data platforms are designed for cost efficiency and scalability, actively identifying and implementing opportunities to optimize cloud spend.
Product-Centric Collaboration: Collaborate with engineering, product, data science, and security teams to translate product requirements and business needs into a strategic data architecture that drives product innovation.
Design & Governance: Conduct deep architecture reviews, assess technical risks, and provide recommendations to ensure data quality, security, and governance are embedded into every product.
Standardization & Enablement: Define and standardize data modeling practices, governance frameworks, and data pipeline patterns to enable efficient and consistent data development across product teams.
Technology Evolution: Evaluate new data technologies, tools, and methodologies (e.g., streaming platforms, modern data warehouses) to continuously improve our data platforms.
Documentation & Mentorship: Document architectural decisions, data flow diagrams, and cost models. Act as a mentor and technical authority, fostering a culture of technical excellence and cost-awareness.

We are assembling a highly skilled, small-scale engineering team focused on transforming generative AI innovation into real, production-grade platforms.
As a Platform Engineer with a strong backend orientation, you will architect and implement the core infrastructure that enables rapid deployment, experimentation, and scaling of advanced AI capabilities. Your work will bridge cutting-edge research with reliable, secure, high-performance systems powering the next generation of digital intelligence products.
Responsibilities:
Design and develop backend services and APIs for SaaS applications using Node.js and TypeScript
Architect and implement microservices and distributed systems optimized for scalability and maintainability
Build and maintain CI/CD pipelines for automated deployments and testing
Develop cloud-native solutions leveraging AWS services and Kubernetes (EKS)
Manage infrastructure as code using Terraform and Helm for Kubernetes deployments
Ensure system reliability, security, observability, and performance at scale
Collaborate with cross-functional teams to deliver features in an agile environment
Continuously improve platform architecture and development workflows.

Required Senior Cloud Security Architect
Position Overview:
As a Cloud Security Architect, you will be responsible for defining and strengthening the security posture of our products and cloud environments. You will lead threat modeling, risk assessments, and the design of secure architectures, while guiding teams in implementing effective security controls and secure development practices. Working closely with developers, engineers, and management, you will ensure security is embedded throughout the product lifecycle and clearly communicate complex concepts across the organization. This role requires strong technical expertise, strategic thinking, and a proactive approach to emerging threats.
Key Responsibilities:
Conduct Threat Modeling and Security Risk Assessment to identify weaknesses in existing security measures and develop strategies to address them.
Design Security Architecture that withstand attacks and ensure the confidentiality, integrity, and availability of the product. This involves establishing secure configurations, access controls, authentication mechanisms, and encryption methodologies.
Implementing Security Controls guiding the integration of secure coding practices, establishing secure development lifecycles, and ensuring adherence to established security standards.
Collaborate with stakeholders including developers, engineers, and management teams. Communicate complex security concepts in a clear and concise manner, ensuring that all parties understand the importance of incorporating security measures into the product development process.
Stay updated with emerging threats and remain vigilant, continuously monitoring emerging threats and vulnerabilities.

We are seeking a Senior Backend & Data Engineer to join its SaaS Data Platform team.
This role offers a unique opportunity to design and build large-scale, high-performance data platforms and backend services that power our cloud-based products.
You will own features end to end-from architecture and design through development and production deployment-while working closely with Data Science, Machine Learning, DevOps, and Product teams.
What Youll Do:
Design, develop, and maintain scalable, secure data platforms and backend services on AWS.
Build batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS.
Develop backend components and data-processing workflows in a cloud-native environment.
Optimize performance, reliability, and observability of data pipelines and backend services.
Collaborate with ML, backend, DevOps, and product teams to deliver data-powered solutions.
Drive best practices, code quality, and technical excellence within the team.
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing).
Tech Stack:
AWS Services: S3, Lambda, Glue, Step Functions, Kinesis, Athena, EMR, Airflow, Iceberg, EKS, SNS/SQS, EventBridge
Languages: Python (Node.js/TypeScript a plus)
Data & Processing: batch & streaming pipelines, distributed computing, serverless architectures, big data workflows
Tooling: CI/CD, GitHub, IaC (Terraform/CDK/SAM), containerized environments, Kubernetes
Observability: CloudWatch, Splunk, Grafana, Datadog
Key Responsibilities:
Design, develop, and maintain scalable, secure backend services and data platforms on AWS
Build and operate batch and streaming ETL/ELT pipelines using Spark, Glue, Athena, Iceberg, Lambda, and EKS
Develop backend components and data processing workflows in a cloud-native environment
Optimize performance, reliability, and observability of data pipelines and backend services
Collaborate with ML, backend, DevOps, and product teams to deliver data-driven solutions
Lead best practices in code quality, architecture, and technical excellence
Ensure security, compliance, and auditability using AWS best practices (IAM, encryption, auditing)

We are looking for an AI Quality & Evaluation Engineer to own the quality planning and execution of an AI-powered chat application operating over complex law enforcement and mobile device data.
This is a highly hands-on role focused on execution rather than high-level QA strategy. You will design, build, and run automated and semi-automated tests for LLM-driven workflows, create evaluation datasets, and continuously stress the system with realistic and extreme investigative scenarios.
What you will be doing:
Design, plan, and execute quality tests for an AI chat application built on LLMs and investigative data.
Build and maintain automation frameworks for prompt regression testing, multi-turn conversations, and model upgrades.
Create and curate evaluation datasets used for regression testing, benchmarking, and model comparison.
Design complex investigative scenarios including ambiguous, incomplete, or conflicting datasets.
Execute manual exploratory testing to uncover hallucinations, reasoning failures, and edge cases.
Work closely with engineering, product, and data teams as part of the development lifecycle.
Validate release readiness and identify regressions related to prompts, models, or data pipelines.
What makes this role different:
You are evaluating AI behavior rather than fixed expected outputs.
You help define what correctness and quality mean for AI reasoning over sensitive data.
You actively invent scenarios to stretch and break the system.
Your work directly impacts trust, reliability, and investigative confidence.

We are looking for a QA Automation Engineer to join our Viewer team and help ensure the reliability, scalability, and performance of our web applications. In this role, you will design and maintain automation frameworks, develop end-to-end tests, and proactively identify issues before they impact our users. You will also be responsible for production releases and managing production bugs, ensuring smooth deployments and quick resolution of critical issues. This position requires strong technical expertise, self-management, and excellent communication skills to collaborate effectively across teams.
Key Responsibilities:
Design and maintain robust test automation frameworks using JavaScript/TypeScript.
Develop and execute automated tests leveraging tools such as Playwright, Selenium, or Cypress.
Collaborate with developers, product managers, and designers to embed quality throughout the development lifecycle.
Debug complex issues using browser DevTools, network logs, and other diagnostic tools.
Integrate automated tests into CI/CD pipelines in partnership with DevOps and engineering teams.
Drive quality initiatives by identifying gaps and proposing improvements in testing processes.

Required Full Stack GenAI Engineer
Position Overview:
We are assembling a small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As a Senior Full Stack GenAI Engineer, you will be a critical architect of the technological infrastructure that brings our most ambitious GenAI concepts to life, transforming our digital intelligence solutions through cutting-edge AI innovation.
What youll love about your mission:
You are more than a developer, you are an innovation catalyst who will:
Transform abstract GenAI concepts into tangible, functional web applications
Design and develop flexible, scalable platforms that can rapidly prototype AI-driven solutions
Create intuitive interfaces that showcase the transformative potential of our AI technologies
Build the technological bridge between complex AI research and user-friendly product experiences
Experiment fearlessly with emerging technologies to push the boundaries of what's possible
What sets this role apart: Innovation at the Intersection of Technology:
You'll be working at the forefront of GenAI product development
Every line of code you write has the potential to unlock a breakthrough GenAI solution
Your technical expertise will directly impact the future of digital intelligence technologies
Exploration and Innovation:
Develop adaptive web architectures that can quickly integrate new GenAI capabilities
Experiment with cutting-edge frontend and backend technologies
Create flexible systems that can evolve with rapidly changing GenAI technologies
Collaborate closely with AI/GenAI researchers to translate complex concepts into user-friendly interfaces.

We are looking for a highly skilled and motivated DevOps Engineer to lead automation initiatives and enhance the efficiency, quality, and scalability of our engineering ecosystem. In this role, you will own the end-to-end CI/CD workflow, build advanced automation for large-scale deployments, and collaborate closely with R&D teams to ensure seamless and secure delivery processes. You will design and implement cloud-based infrastructure, integrate automated testing frameworks, and drive continuous improvements across development, deployment, and operations. This position is ideal for someone who thrives in dynamic, modern environments, enjoys solving complex technical problems, and plays a critical role in elevating our engineering velocity and product reliability.
Responsibilities:
Drive automation across infrastructure and deployment systems.
Improve and shorten processes to help engineering and operations teams work smarter and faster with high quality.
Design, develop, and modify automation processes for deploying large-scale, enterprise-grade applications.
Serve as an expert in R&D CI/CD processes throughout the software development lifecycle.
Manage CI/CD processes on the cloud and on Windows and Linux servers.
Collaborate with R&D teams to integrate testing automation into CI/CD workflows.
Setting up tools and required infrastructure.
Becoming an expert in highly secured web applications.
Working closely with other DevOps engineers and developers to remediate findings and provide solutions.

Required Data Engineer
Position Overview:
We are assembling an elite, small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As a Senior Data Engineer, you will be the critical data backbone of our innovation engine, transforming raw data into the fuel that powers groundbreaking GenAI solutions, driving our digital intelligence capabilities to unprecedented heights.
Your Strategic Role:
You are not just a data engineer - you are a strategic enabler of GenAI innovation. Your primary mission is to:
Prepare, structure, and optimize data for cutting-edge GenAI project exploration
Design data infrastructures that support rapid GenAI prototype development
Uncover unique data insights that can spark transformative AI project ideas
Create flexible, robust data pipelines that accelerate GenAI research and development
What Sets This Role Apart:
Data as the Foundation of AI Innovation
You'll be working at the intersection of advanced data engineering and generative AI
Your data solutions will directly enable the team's ability to experiment with and develop novel AI concepts
Every data pipeline you design has the potential to unlock a breakthrough GenAI project
Exploration and Innovation
Conduct deep data exploration to identify potential GenAI application areas
Work closely with AI researchers to understand data requirements for cutting-edge GenAI projects.

We are seeking a QA Engineer with a strong passion for data quality, performance, and scale to join our Data Platform team.
This role is ideal for a QA professional who enjoys working close to complex data systems, understands large-scale pipelines, and wants to play a key role in shaping the automation and quality strategy of a data engineering organization.
You will act as the primary quality owner for high-volume, mission-critical data platforms, working closely with data engineers, backend developers, and platform teams.
What Youll Do:
Data Quality & Validation:
Design and execute data validation strategies for large-scale batch and streaming pipelines
Ensure data correctness, completeness, freshness, and consistency across the data lake
Define and automate checks for schema changes, data drift, and data quality regressions
Performance & Scalability Testing:
Plan and execute performance and scalability tests for data pipelines and processing jobs
Identify bottlenecks across ingestion, transformation, and querying layers
Partner with engineers to validate performance improvements and prevent regressions
Automation & Infrastructure:
Develop and maintain the data teams QA automation infrastructure
Build reusable testing frameworks and tools tailored for large datasets and pipelines
Integrate automated tests into CI/CD pipelines and production monitoring workflows
Collaboration & Ownership:
Work closely with data engineers, backend developers, and platform engineers throughout the development lifecycle
Act as the sole QA owner within a cross-functional team, driving quality without becoming a bottleneck
Participate in design discussions to ensure testability and observability are built in from the start
Quality Mindset & Communication:
Champion a quality-first culture within the team
Clearly communicate risks, findings, and quality metrics to technical stakeholders
Balance thoroughness with pragmatism in fast-moving, high-scale environments.

Required AI Platform Engineer
Position Overview:
We're assembling a small-scale team of innovators committed to a transformative mission: advancing generative AI from conceptual breakthrough to tangible product reality. As an AI Platfrom Engineer, you will be a critical architect of the technological infrastructure that brings our most ambitious GenAI concepts to life, transforming our digital intelligence solutions through cutting-edge AI innovation.
Build advanced AI platform that operates both as a cloud SaaS and as a fully self-contained on-prem / edge deployment, designed for privacy-sensitive and security-critical environments, at the intersection of backend development, AI integration, DevOps, and open-source systems engineering.
You will be part of the core team responsible for adapting, hardening, and operating our SaaS architecture in on-prem and single-node environments (on Prem servers, laptops). Working closely with architecture and product management and play a key role in making complex AI systems deployable, reliable, and operable outside the cloud.
Key Responsibilities
Platform & Application Engineering:
Adapt cloud-native AI services to on-prem and edge deployments (single node, no managed cloud services).
Build and maintain full-stack components: Backend APIs (Python / Node.js), Lightweight UIs or internal tools when needed, Ensure services are stateless, configurable, and portable across environments.
AI & Open-Source Integration:
Integrate and operate open-source LLMs for:
RAG pipelines
Agentic workflows
Tool calling and orchestration
Work with: Embedding models, Vector databases (local and embedded modes), Analytical engines (e.g., embedded SQL / columnar systems), Optimize inference for CPU / single-GPU environments (quantization, batching, caching).
DevOps & Runtime Engineering (Strong Focus):
Package services into portable Docker containers usable in:
On-prem servers (Kubernetes)
laptop / edge devices
Implement in-process scaling strategies (worker pools, task queues, batching).
Build simple, reliable deployment and startup flows (no heavy orchestration).
Manage configuration, secrets, logging, and observability in constrained environments.
Systems & Reliability:
Design for: Offline operation, Limited resources, Predictable performance
Implement graceful degradation between: SaaS mode, On-prem server mode, Single-node / laptop device mode, Debug complex interactions across AI models, storage, and runtime systems.

We are looking for a talented and driven developer to join our Research Engineering team and contribute to the development of scalable, cloud-native AI solutions on AWS. This role focuses on building and maintaining infrastructure and services that support advanced machine learning workflows, real-time inference, and robust observability.
You will research and build data-driven applications. Research and develop Machine Learning algorithms to turn forensic data into investigation leads, evidence, and intelligence insights. Be a part of a heterogeneous, multi-disciplinary research team. Take projects end to end, from the inception of the idea, through data and algorithm research and POC development. The work is both analytical and experimental in nature and includes prototyping of new algorithms, investigating data, and evaluating algorithm performance.
Responsibilities:
Design and implement features for our AWS-based AI solution, including job orchestration, manifest generation, and API integrations.
Develop and maintain CI/CD pipelines using GitHub Actions, CDK, and AWS infrastructure (e.g., SageMaker, Lambda, Bedrock).
Ensure code quality and reliability through comprehensive unit testing, performance testing, and observability enhancements.
Collaborate with cross-functional teams to integrate AI services into broader investigation workflows and runtime environments.
Troubleshoot deployment issues and contribute to the continuous improvement of dashboards and monitoring tools.

Required AI Engineer
About The Position
Company Overview:
We are a global leader in digital intelligence solutions, empowering law enforcement, intelligence agencies, and enterprises to protect and save lives, accelerate justice, and make communities safer.
Our AI-powered Digital Intelligence Platform enables lawful access, collection, analysis, and sharing of digital evidence, while preserving data privacy and ensuring compliance.
Our solutions are trusted by thousands of agencies and organizations worldwide, across cloud, on-premises, and hybrid deployments.
Position Overview:
The Forensic Research Group (FRG) is seeking a highly skilled AI Engineer to help define the future of intelligent forensic research platforms.In this role, you will lead the design and integration of advanced AI capabilities into a large-scale, production-grade environment, working closely with core engineering and research teams.
You will contribute to unifying internal tools and workflows into a cohesive, AI-driven ecosystem that significantly enhances developer and researcher productivity.You will also drive the evolution of automation and analysis pipelines, replacing brittle processes with robust, scalable, and intelligent solutions.
A key part of the role involves exploring complex datasets, evaluating models, and applying generative AI and heuristic approaches to uncover, structure, and interpret digital artifacts.This position offers the opportunity to work on challenging problems at the intersection of AI, systems engineering, and data analysis, with real influence over architecture, tooling, and research direction.
If you are motivated by building high-impact AI systems, solving non-trivial technical problems, and enabling teams to operate at a higher level, this role provides a unique opportunity to make a lasting impact in a mission-driven domain.
Key Responsibilities:
Develop and implement AI solutions to parse and analyze data from forensic extractions, including mobile devices.
Design, build, test, and maintain efficient, reusable, and reliable C# .NET code with integration to cloud services in AWS.
Utilize heuristic-based methods and GenAI technologies to enhance data identification and classification.
Research, explore data, assess, and implement the best models to solve various forensic research problems.
Collaborate with other professionals across the company, combining AI, Forensic Research, and Engineering expertise.
Translate forensic research methods into AI algorithms and innovation suggestions.