Role & responsibilities - Architect & Delivery Expert Embedded Systems & AI

Preferred candidate profile

Key Responsibilities

- Design and define end-to-end technical and solution architecture aligned with business and engineering requirements.
- Provide architecture and technical leadership for embedded systems, firmware, software platforms, cloud services, AI-enabled applications, and engineering tools.
- Hands-on experience with Embedded C/C++, Python, Linux, device interfaces, firmware, hardware-software integration, debugging, and system-level validation.
- Work with embedded hardware, SoCs, microcontrollers, processors, communication interfaces, and low-level software components.
- Support hardware/software integration, bring-up activities, debugging, performance optimization, and production issue resolution.
- Hands-on experience with Artificial Intelligence, Generative AI, Large Language Models (LLMs), AI agents, prompt engineering, RAG, automation, and AI-assisted engineering workflows.
- Integrate LLMs and AI APIs into applications and internal engineering platforms.
- Develop AI-powered automation solutions for analysis, debugging, verification, documentation, root-cause analysis, and productivity improvement.
- Evaluate and work with different AI models, APIs, frameworks, and deployment approaches based on accuracy, latency, cost, and scalability requirements.
- Build Python-based automation and AI integration workflows for engineering and delivery use cases.
- Design scalable APIs,



services, microservices, integrations, and data-processing pipelines.
- Prepare architecture documents, solution designs, technical specifications, proof-of-concepts, and implementation roadmaps.
- Lead complete project delivery from requirement analysis, estimation, architecture, development, testing, validation, release, and production deployment.
- Coordinate with embedded developers, software engineers, QA/verification teams, DevOps, product teams, vendors, customers, and other stakeholders.
- Drive Agile/Scrum delivery, sprint planning, milestone tracking, release management, risk management, and stakeholder communication.
- Establish development, architecture, security, quality, and engineering best practices.
- Conduct technical and architecture reviews and guide engineering teams on complex implementation decisions.
- Identify technical risks, dependencies, performance bottlenecks, and delivery challenges and drive them to resolution.
- Support CI/CD, DevOps, automation, cloud deployment, containerization, and software release processes.
- Troubleshoot complex embedded, software, AI integration, and production issues.
- Mentor engineers and promote knowledge sharing, technical excellence, and adoption of contemporary AI-driven development practices.
- Work closely with customers and senior management to ensure technical solutions meet business objectives, quality expectations, and delivery commitments.

📌 Iot Solution Architect (Ahmedabad)
🏢 VeriFast Technologies
📍 Ahmedabad