Applied AI Engineer

Applied AI Engineer Location: Bengaluru, India (Residency Road, In-Office, Full-Time) Reports to: Engineering Manager, Bengaluru About neuroGrid neuroGrid is a well-funded startup building a next-generation SaaS platform to accelerate the development of modern, low-cost power plants and AI infrastructure—including data centers, solar, wind, battery storage, nuclear, and transmission. Energy is the world’s largest and most critical industry—and it’s undergoing a once-in-a-century transformation driven by rapid AI datacenter expansion. Our AI-powered platform is built to meet this moment. By transforming fragmented data, manual workflows, and institutional knowledge into a single intelligent work orchestration system, we help energy and data center developers move faster, reduce costs, and make better decisions. Our product strategy is intentionally broad and ambitious, supporting users across multiple domains—land control, interconnection, permitting, engineering, finance, stakeholder engagement, and more. The Role We are seeking an experienced Applied AI Engineer with proven experience embedding AI/ML technologies into enterprise software. You will play a critical role in building our MVP from the ground up, working closely with US and India teammates to design, develop, and ship features end-to-end. This is a unique opportunity for someone who thrives in an early-stage environment, enjoys the energy of building all new AI-enabled applications, and is motivated to shape both the product and the engineering culture. Responsibilities Full-stack delivery: Design, develop, and ship features across the data stack and applying enterprise SaaS best practices. AI integration: Transform user workflows to accelerate and simplify client tasks with AI and ML tooling. Product collaboration: Partner with Product and Design to translate customer workflows into performant, elegant product experiences. Technical quality: Own testing, reliability, observability, and security for the models and features you ship. Architecture & reviews: Contribute to system design and code reviews; help set engineering patterns that scale for AI. Customer focus: Engage with external users to validate assumptions and iterate quickly. Culture & collaboration: Model high ownership, humility, and teamwork; contribute to strong engineering team culture and collaboration. Requirements 5+ years of professional experience in engineering (enterprise SaaS preferred) and/or AI/ML products. Excellent communicator, comfortable collaborating across cultures and time zones.Hands-on experience integrating LLMs, vector databases, RAG pipelines, and AI-powered workflows. Solid data expertise: relational + NoSQL databases, data modeling, indexing, and performance optimization. Proficiency with cloud platforms (AWS/Azure/GCP), containerization, CI/CD, and infrastructure-as-code. Track record of delivering in fast-moving, ambiguous environments. Bonus Experience with energy sector workflows (utility-scale renewables, data centers, grid infrastructure, etc.). Strong proficiency in React + TypeScript on the front end, and Python/Node.js on the back end. Background in geospatial data, enterprise document systems, or integrations. Familiarity with secure-by-default enterprise SaaS practices. Compensation & Growth Competitive cash salary plus meaningful equity in a fast-growing startup. As an early member of neuroGrid’s engineering core, you’ll have significant ownership and the opportunity to directly shape both the product and the company’s future. Significant upside as the platform and team scales, with scope to expand your role and impact over time. How to Apply If you’re excited to build innovative software from the ground up and embed AI where it truly moves the needle, we’d love to hear from you. Please send your resume and a brief note about your experience and interest in neuroGrid to: Erik Langenborg ( ) and Jack Fisher ( ).