Jobs at Striveworks

The Junior Quality Engineer will verify software performance, document test results, develop and implement testing strategies, and improve product quality. The role involves applying software testing methodologies, communicating technical findings, and building knowledge of software, data science, and machine learning systems. Test automation, programming, databases, CI/CD, containerization, and security clearance experience are preferred. The position is hybrid or on-site in Austin, Texas.

Develop machine learning capabilities, custom analytics, and mission-critical AI solutions across image, video, text, geospatial, time-series, and structured data. Build and orchestrate data engineering pipelines for agentic and traditional architectures, collaborate with data scientists, software and DevOps engineers, contribute to the Chariot AI operations platform, and support customer-facing deployments.

Develop quality software for AI systems that monitor model performance, manage drift, and support reliable production deployment. Contribute to cloud-neutral, microservices-based platforms using event-driven architecture, infrastructure as code, databases, APIs, and cloud technologies. Collaborate with an experienced engineering team, solve meaningful problems, and grow technical skills. The role is hybrid or on-site in Austin, Texas, and requires U.S. person status.

Build and style front-end UI/UX components for core AI products using TypeScript, JavaScript, React, CSS, and REST APIs. Collaborate with UX designers, data scientists, and software engineers to solve complex problems, integrate backend services, and deliver reliable web applications. The role supports technical growth and requires strong problem-solving skills, Git experience, U.S. person status, and hybrid/on-site work in Austin, Texas.

Own and maintain product marketing collateral for an AIOps platform, agentic AI orchestrator, and vertical solutions. Translate technical input from product and data science teams into polished presentations, graphics, diagrams, and decision-ready materials. Align messaging with Communications, support government and industry conference operations, develop technical content, and track customer feedback, market trends, competitors, and emerging technologies. The role requires credible communication with technical evaluators and senior government decision-makers.

As a Senior Software Engineer, you will develop, deploy, and maintain production ML models, lead projects, and collaborate across teams using various programming languages and tools.

Own the legal operations and contract execution lifecycle, including triage, review, negotiation, tracking, and management of commercial, public sector, vendor, licensing, teaming, subcontract, and NDA agreements. Translate FAR and DFARS requirements into operational procedures, improve contract lifecycle workflows, maintain legal databases, manage federal compliance, protect intellectual property, and support scalable legal operations. Collaborate with business development, engineering, security, IT, and leadership while managing sensitive information and supporting the company’s growth.

As a Staff Machine Learning Engineer, lead teams in designing AI solutions, managing projects, and interfacing with clients while ensuring technical excellence and operational effectiveness.

The Staff Machine Learning Engineer will lead the development of AI solutions, ensure project delivery, and manage technical teams while interfacing with customers. Responsibilities include designing data pipelines, overseeing machine learning model development, and facilitating customer engagement.

Design and deploy production-grade machine learning models and data pipelines across image, video, text, geospatial, time-series, and structured data. Collaborate with customers, data scientists, software and DevOps engineers to define requirements, maintain mission-critical deployments, and contribute to the Chariot AI operations platform.

Design, validate, and deploy machine learning models and custom analytic algorithms across image, video, text, geospatial, time-series, and structured data. Work with engineers to implement AI solutions for cloud and edge, monitor model performance, manage drift, and sustain production systems in secure government environments.

Lead product vision and roadmap for AI infrastructure and agentic systems. Work with engineering, data science, and sales to define requirements, prioritize features, enable execution, validate deliverables, maintain technical documentation, support go-to-market launches, and track customer feedback and market trends to drive platform strategy and measurable outcomes.

As a Machine Learning Engineer, you will develop machine learning models, automate data engineering pipelines, and support customer-centric projects while collaborating with data scientists and engineers.

As a Data Scientist, you'll develop and validate machine learning models, implement AI solutions, and conduct fieldwork in support of customers.

The Senior DevOps Engineer will manage AI deployments, enhance cloud environments, implement Infrastructure-as-Code, and ensure software reliability while guiding junior team members.