Lead AI Software Engineer

About EnCharge AI

EnCharge AI is building the next generation AI platform. Our novel in-memory-computing architecture delivers a 10x step-function improvement in compute energy efficiency and performance for AI inference workloads. As the demands of artificial intelligence move beyond today's models, we believe fundamental underlying infrastructure must evolve. We are an experienced team of AI researchers, silicon & systems engineers, and architects backed by leading investors, poised to become the essential platform for the next wave of AI innovation.

The Opportunity

Video generation represents one of the most compute-intensive frontiers in AI—and one of the most promising applications for our hardware's energy efficiency advantages. We're building a vertically-integrated video generation stack that will showcase the transformative potential of our silicon while delivering real value to customers today.

We are seeking a Software Engineer to build the infrastructure and applications that bring our video generation capabilities to market. You'll build the serving stack, customer-facing APIs, and develop agentic systems that demonstrate what's possible when video generation meets energy-efficient hardware.

This is a foundational role. You won't be inheriting a mature codebase—you'll be architecting production systems from scratch, making critical technical decisions, and building software that directly enables our go-to-market motion.

Key Responsibilities

• Inference & Serving Infrastructure: Design and build scalable serving infrastructure for video generation models (Wan, LTX-Video, Flux, and beyond). Own latency, throughput, reliability, and cost optimization.
• API & Platform Development: Build robust APIs and SDKs that enable customers and partners to integrate video generation into their products. Design abstractions that balance flexibility with ease-of-use.
• Video Applications & Demos: Develop compelling demo applications that showcase our platform's capabilities—interactive experiences, batch processing workflows, and vertical-specific solutions that support the GTM team.
• Agentic Workflows: Build agentic systems that leverage video generation as a core capability—autonomous video editing pipelines, multi-step generation workflows, and tool-use patterns that extend what's possible with video AI.
• Production Operations: Establish monitoring, observability, and deployment practices for video generation workloads. Ensure systems are reliable, debuggable, and ready for customer-facing use.

Qualifications

• 7-12 years of software engineering experience, with a focus on backend systems or ML infrastructure
• Strong fundamentals in Python and at least one systems language (Go, Rust, C++)
• Experience building and operating production APIs and serving systems
• Familiarity with ML inference pipelines (model serving, GPU workloads, batching strategies)
• Comfort working in fast-moving, ambiguous environments where you define the roadmap
• Strong product instincts—you think about how software will be used, not just how it works

Nice to Have

• Experience with video processing pipelines or media infrastructure
• Background building agentic systems or multi-step AI workflows
• Familiarity with diffusion models or generative AI systems
• Experience with Kubernetes, Ray, or other orchestration frameworks
• Track record shipping developer tools or APIs