We are looking for a** FullStack Engineer **with a strong backend focus to help build and scale Enterprise products. You will work closely with Product and Engineering teams to develop partner-facing experiences, widgets, and internal applications. **Responsibilities - Build and maintain frontend applications, widgets, partner portals, and landing pages. - Design and implement backend services and APIs. - Prototype new partner integrations and B2B solutions. - Work closely with Product Managers and Designers from requirements to production. - Own features end-to-end, including deployment and support. - Participate in code reviews and architecture discussions. - Actively leverage AI tools to accelerate development and increase productivity.

• Design, implement, and maintain APIs, services, and distributed systems that form the backbone of Gigawatt OS. • Collaborate with AI engineers to integrate models, embeddings, and agent services into backend systems. • Operate AI APIs, ensuring outputs are production-ready and aligned with enterprise utility requirements. • Transform legacy workflows into modern, secure, scalable codebases using cloud-native best practices. • Partner with security leaders to ensure all services adhere to stringent utility-sector regulations, implementing secure coding practices by default. • Deliver features and improvements in cycles measured in weeks, balancing speed with reliability.

• Design, develop, and maintain Adobe Experience Manager (AEM) components, templates, services, and integrations • Develop front-end and back-end functionality using Java, HTL, JavaScript, HTML, and CSS • Configure and enhance AEM content authoring experiences and workflows • Troubleshoot and resolve defects, performance issues, and production incidents • Contribute to technical improvements, platform upgrades, and continuous optimization initiatives • Act as the primary technical point of contact within the Scrum team • Support solution design and ensure alignment with AEM best practices and HBK technical standards • Review code and deliverables from external development partners • Help refine technical requirements and estimate development efforts • Identify technical risks and propose practical solutions • Promote code quality, maintainability, security, and performance standards • Work closely with HBK's Cyber Security team to ensure digital solutions meet corporate security standards and policies • Collaborate with Cyber Security and Infrastructure teams on authentication, authorization, data protection, and secure integrations • Participate in Scrum ceremonies including sprint planning, backlog refinement, daily stand-ups, reviews, and retrospectives

• Define and maintain the technical architecture, establishing pragmatic patterns and guardrails that accelerate rapid, high-quality feature delivery. • Lead the technical execution for migrating, decoupling, and modernizing legacy systems, owning the sequencing, risk mitigation strategies, and target-state designs to extract core business domains seamlessly. • Establish the core shared framework for integrating agentic workflows, intelligent automation, and LLM orchestration across the platform with strict compliance auditability and AI API latency under 100 ms. • Act as the definitive technical authority to proactively resolve cross-team architectural dependencies and ensure alignment across infrastructure and codebases. • Collaborate with Product leadership and the VP of Engineering to translate business milestones into an actionable technical roadmap, grounding technical debt reduction directly in business outcomes. • Author and embed standardized design templates into the software development lifecycle that leverage AI-assisted tools, driving 100% adoption across engineering pods and reducing cycle times by 35% or more. • Work closely with development, QA, and security teams to ensure architectural blueprints are highly practical, realistic, and friction-free for execution. • Design and implement LLM routing, caching, and model-governance architectures that optimize AI infrastructure costs to remain within 10% of the quarterly budget.