What You'll Do
Collaborate with stakeholders to identify real-world problems and translate them into actionable technical strategies. Design and implement scalable AI solutions from concept to deployment, ensuring alignment with customer objectives and platform capabilities.
Orchestrate data workflows across cloud-native, event-driven architectures, automating pipelines that process diverse data types including imagery, video, text, and time series. Develop and refine machine learning models using modern frameworks, tailoring approaches to specific operational needs.
Lead cross-functional teams through full project lifecycles, contributing directly to code and architecture while mentoring others. Communicate technical direction clearly to both technical and non-technical audiences, ensuring transparency and alignment across teams and customer sites.
Identify systemic improvements, advocate for reusable components, and help shape long-term technical strategy. Conduct on-site engagements when necessary to ensure solutions meet mission requirements.
Requirements
- Advanced degree in machine learning, computer science, data science, or a closely related field
- Minimum of 10 years of hands-on experience in building and deploying production-grade AI and data systems
- Strong command of Python and common ML libraries such as TensorFlow, PyTorch, and scikit-learn
- Proficiency in systems programming languages including Go, Rust, C++, Java, or Scala
- Proven ability to design robust algorithms, data structures, and analytics pipelines for production environments
- Experience applying software design patterns in cloud platforms and distributed systems
- Track record of scoping and delivering complex technical projects on time and with measurable impact
- Familiarity with Agile methodologies, version control, CI/CD, and modern software engineering practices
- Demonstrated leadership in managing and guiding technical teams across remote and on-site settings
- Ability to explain complex concepts clearly through writing, speaking, and presentations
- Eligibility and willingness to obtain and maintain a US Secret security clearance
- US citizenship required
Preferred Qualifications
- Hands-on experience with Kubernetes and large-scale distributed systems
- Working knowledge of messaging platforms such as Kafka, NATS, or RabbitMQ
- Experience developing AI agents and automated decision workflows
- Exposure to specialized data types like full motion video, multi-spectral imagery, sonar, radar, or hardware telemetry
- Background delivering solutions within secure government or defense environments
- Active US security clearance at the Secret level or higher
Technical Environment
Work across a modern stack including Python, TensorFlow, PyTorch, scikit-learn, and systems languages like Go and Rust. Operate in cloud-native environments leveraging Kubernetes, microservices, and event-driven architectures with messaging layers such as Kafka or NATS.
Benefits
- Comprehensive medical, dental, and vision insurance
- Voluntary benefits including life, long-term disability, accident, and hospital indemnity coverage
- Health Savings Account (HSA) and Flexible Spending Account (FSA) options, including dependent care FSA
- 401(k) retirement plan with company matching
- Unlimited paid time off
- Paid parental leave
Compensation
Base salary range of $200,000–$250,000 per year, supplemented by equity grants and performance-based cash bonuses.
Work Mode
This role is based in northwest Austin, TX, with a hybrid structure. While the team supports a fully remote work environment, occasional travel—up to 20% of the time—may be required for on-site collaboration or customer engagements.
Culture
Work in a high-trust environment where ownership and initiative are expected. Contribute to a culture grounded in mutual respect, candid yet constructive communication, and shared responsibility for outcomes. The team values perseverance, purpose-driven work, and the satisfaction of tackling meaningful challenges together.
