Principal Solutions Engineer

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is looking for a highly experienced, hands-on Principal Solutions Engineer to lead customer and partner solution development, architecture, and deployment for our next-generation AI acceleration platform. This is a senior technical leadership role that combines customer-facing engagement, solution architecture, AI software optimization, and technical mentorship. This role will partner with strategic customers throughout their development lifecycle—from initial technical discovery, architectural evaluation, and proof-of-concepts through production deployment and scaling. Bridging the gap between AI hardware, software, systems, and customers, helping them successfully build, optimize, and scale cutting-edge AI workloads and agentic workflows on EnCharge technology. Serving as the voice of the customer, directly influencing product roadmaps, software features, and developer experience. Responsibilities Serve as the primary technical interface and trusted advisor for strategic customers and partners evaluating and deploying AI workloads on EnCharge platforms. Lead end-to-end customer engagements from technical discovery through proof-of-concept (PoC), design-in, performance benchmarking, system-level tuning, and production deployment. Support technical pre-sales efforts by clearly articulating solution value propositions, architectural differentiators, and competitive performance benchmarks. Architect and develop reference applications, demonstrations, solution accelerators, and customer evaluation platforms for diverse verticals (e.g., edge AI, robotics, autonomous systems, enterprise datacenter). Help customers integrate complex AI models, perception pipelines, multi-modal systems, AI agents, and software stacks into robust end-to-end solutions. Proactively identify and onboard strategic software and hardware partners, mapping value chains to co-develop AI solutions that expand market reach and accelerate time-to-market. Collaborate with ODMs on complete system designs and collaborate with ISVs to deliver documentation and reference designs that empower the ecosystem. Troubleshoot complex hardware/software integration challenges, optimizing application performance, latency, throughput, and power efficiency to drive winning proof points. Partner closely with Product Management and Engineering to communicate requirements, identify product gaps, and directly influence the product roadmap. Develop comprehensive technical documentation, application notes, tutorials, training materials, and enablement collateral. Required Qualifications 8+ years of experience in Solutions Engineering, Field Applications Engineering, Technical Marketing Engineering, or related customer-facing technical roles within the semiconductor or AI industry. Proven track record of bringing complex hardware and software products to market and driving adoption through end-to-end solution integration. Strong software development experience using Python and C++. Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, ONNX Runtime, or similar, as well as AI inference optimization and model deployment. Strong understanding of AI workloads, optimization, heterogeneous SoC architectures, software stacks, and system integration. Experience working with embedded Linux systems, heterogeneous compute platforms, or AI accelerators. Outstanding communication and interpersonal skills, with the ability to explain complex technical concepts clearly to diverse technical and executive audiences. Self-motivated, execution-oriented mindset with a strong customer-first approach to solving complex technical challenges. Preferred Qualifications Master’s or Ph.D. in Electrical Engineering, Computer Science, or a related field preferred. Knowledge of AI agents, agentic workflows, multi-modal AI systems, or LLM-based edge applications. Backgrou