Asks for

The ad says“7+ years of professional software engineering experience, including 3+ years shipping AI/ML-powered products into production”
The ad says“Strong knowledge of APIs and modern software design patterns for integrating AI into SaaS products”
The ad says“Experience architecting scalable systems on cloud platforms (AWS, Azure, GCP)”
The ad says“Experience architecting scalable systems on cloud platforms (AWS, Azure, GCP)”
The ad says“Ensure reliability, scalability, and maintainability of all systems in production, leveraging CI/CD and cloud-native workflows”
The ad says“Experience architecting scalable systems on cloud platforms (AWS, Azure, GCP)”
The ad says“Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR)”
The ad says“Expertise in data modeling, preprocessing, and model evaluation at scale”
The ad says“Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications”
The ad says“Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications”
The ad says“Experience architecting scalable systems on cloud platforms (AWS, Azure, GCP)”
The ad says“Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR)”
The ad says“Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications”
The ad says“Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR)”
The ad says“Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications”
The ad says“Understanding of and/or experience with Model Context Protocol (MCP) or similar emerging standards for connecting AI systems with data and tools”
The ad says“Understanding of and/or experience with Model Context Protocol (MCP) or similar emerging standards for connecting AI systems with data and tools”
The ad says“Expertise in data modeling, preprocessing, and model evaluation at scale”
The ad says“Expertise in data modeling, preprocessing, and model evaluation at scale”
The ad says“Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR)”
The ad says“Hands-on experience with retrieval-augmented generation (RAG) for building AI systems that combine large language models with external knowledge sources”
The ad says“Experience building AI systems for real-time, low-latency, or edge deployments”
The ad says“Hands-on experience with retrieval-augmented generation (RAG) for building AI systems that combine large language models with external knowledge sources”
The ad says“Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR)”
The ad says“7+ years of professional software engineering experience, including 3+ years shipping AI/ML-powered products into production”

We’re looking for a Senior Software Engineer with a passion for AI to join us in our mission of bringing the ION Factory OS to next-generation hardware builders around the globe. This role is based in Los Angeles, CA (HQ in El Segundo)
Are you excited by the opportunity to build AI-powered software that accelerates the development of eVTOLs, rockets, robots, and autonomous vehicles?
Lead the design, implementation, and optimization of production-ready AI systems within the ION Factory OS
Ship customer-facing features that directly impact manufacturing workflows, including AI-driven functionality (e.g., generative procedure creation, anomaly detection, recommendations) and core product features not reliant on AI
Architect and maintain scalable software systems, including AI/ML pipelines and broader product infrastructure
Design and implement AI features using retrieval-augmented generation (RAG) pipelines to deliver context-aware insights and recommendations
Leverage Model Context Protocol (MCP) and similar frameworks to connect AI models seamlessly with structured/unstructured data sources and external tools
Collaborate with product managers and customers to translate real-world challenges into robust software solutions
Partner with data engineering to process and transform structured and unstructured manufacturing data into usable formats
Ensure reliability, scalability, and maintainability of all systems in production, leveraging CI/CD and cloud-native workflows
Stay ahead of advancements in software engineering and AI, bringing the best practices into shipped product features
Mentor junior engineers and help raise the technical bar across the team

Benefits

Medical, dental & vision
Generous life and disability insurance for you and your family
Flexible PTO
401K retirement plan with employer match
Other financial benefits and services to give you financial peace of mind
Equity
Up to 16 weeks of parental leave
Flexible spending accounts
Work-from-home setup
Remote & hybrid options (role dependent)
Amazing office in Downtown LA

Preferred experience

Proven track record of building and shipping customer-facing applications (AI and non-AI) that deliver measurable business value
Strong knowledge of APIs and modern software design patterns for integrating AI into SaaS products
7+ years of professional software engineering experience, including 3+ years shipping AI/ML-powered products into production
Expertise in data modeling, preprocessing, and model evaluation at scale
Experience architecting scalable systems on cloud platforms (AWS, Azure, GCP)
Passion for AI innovation paired with the ability to deliver non-AI product functionality when needed
Excellent problem-solving, communication, and cross-functional collaboration skills
Familiarity with generative AI models (LLMs, diffusion models, GANs) and their real-world applications
Experience building AI systems for real-time, low-latency, or edge deployments
Familiarity with modern data governance, privacy, and compliance standards (SOC2, GDPR, ITAR)
Hands-on experience with retrieval-augmented generation (RAG) for building AI systems that combine large language models with external knowledge sources
Understanding of and/or experience with Model Context Protocol (MCP) or similar emerging standards for connecting AI systems with data and tools
Customer-facing experience gathering requirements, presenting solutions, and demonstrating value
Contributions to open-source projects or published research in applied AI/ML
Experience mentoring engineers and contributing to engineering best practices