Iot Solution Architect

Verifast Technologies

Ahmedabad District

On-site

INR 4,000,000 - 6,000,000

Full time

14 days+

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Job summary

Verifast Technologies seeks an Architect & Delivery Expert in Embedded Systems & AI to define end-to-end architectures and provide technical leadership across embedded hardware, firmware, software platforms, cloud services, and AI-enabled applications.

The role involves hands-on work with Embedded C/C++, Python, Linux, and system-level validation, plus driving AI-assisted engineering workflows and development best practices.

Qualifications

  • Proven experience in architecture and delivery of embedded systems projects.
  • Hands-on with embedded C/C++, Python, Linux, and hardware-software integration.
  • Experience in AI/GenAI, LLMs, AI agents, prompt engineering and AI-assisted workflows.

Responsibilities

  • Define and design end-to-end architectures aligned with requirements.
  • Provide technical leadership across embedded systems, firmware, software platforms, cloud services, and AI-enabled apps.
  • Lead hardware/software integration, system bring-up, debugging, and performance optimization.
  • Develop AI-powered automation for analysis, debugging, verification, documentation, and productivity.

Skills

Architectural leadership
Embedded C/C++
Python
Linux
System design
AI integration
Cloud services
Debugging
Agile/Scrum
DevOps
CI/CD

Job description

Role & responsibilities - Architect & Delivery Expert Embedded Systems & AI
Preferred candidate profile :
Key Responsibilities:
  • Define and design end-to-end technical and solution architectures aligned with business and engineering requirements.
  • Provide technical and architectural leadership across embedded systems, firmware, software platforms, cloud services, AI-enabled applications, and engineering tools.
  • Work hands-on with Embedded C/C++, Python, Linux, firmware, device interfaces, hardware-software integration, debugging, and system-level validation.
  • Work with embedded hardware, SoCs, microcontrollers, processors, communication interfaces, and low-level software components.
  • Lead hardware/software integration, system bring-up, debugging, performance optimization, and production issue resolution.
  • Design and implement solutions leveraging AI, Generative AI, LLMs, AI agents, prompt engineering, RAG, and AI-assisted engineering workflows.
  • Integrate LLMs and AI APIs into applications and internal engineering platforms.
  • Develop AI-powered automation for analysis, debugging, verification, documentation, root-cause analysis, and engineering productivity.
  • Evaluate AI models, APIs, frameworks, and deployment approaches based on accuracy, latency, cost, security, and scalability.
  • Develop Python-based automation and AI integration workflows for engineering and delivery use cases.
  • Design scalable APIs, microservices, integrations, and data-processing pipelines.
  • Prepare architecture documents, solution designs, technical specifications, POCs, and implementation roadmaps.
  • Lead projects through the complete delivery lifecycle, including requirements, estimation, architecture, development, testing, validation, release, and production deployment.
  • Collaborate with embedded developers, software engineers, QA/verification, DevOps, product teams, vendors, customers, and other stakeholders.
  • Drive Agile/Scrum delivery, sprint planning, milestone tracking, release management, risk management, and stakeholder communication.
  • Establish and promote development, architecture, security, quality, and engineering best practices.
  • Conduct technical and architecture reviews and provide guidance on complex implementation decisions.
  • Identify and resolve technical risks, dependencies, performance bottlenecks, and delivery challenges.
  • Support CI/CD, DevOps, automation, cloud deployment, containerization, and software release processes.
  • Troubleshoot complex embedded, software, AI integration, and production issues.
  • Mentor engineers, promote knowledge sharing, and drive adoption of modern AI-enabled engineering practices.
  • Work closely with customers and senior management to ensure solutions meet business objectives, quality standards, and delivery commitments.
Core Skills

Architecture & Leadership:
Solution Architecture, Technical Architecture, System Design, Integration Architecture, Technical Leadership, Project Delivery, Stakeholder Management, Risk Management, Release Management

Embedded & Software:
Embedded Systems, Embedded C/C++, Python, Linux, Firmware, SoC, Microcontrollers, Processors, Device Interfaces, Hardware-Software Integration, System Debugging, System Validation, Performance Optimization

AI & GenAI:
Artificial Intelligence, Generative AI, LLMs, AI Agents, Prompt Engineering, RAG, LLM APIs, AI Automation, AI-assisted Engineering, AI Model Evaluation

Cloud & Software Engineering:
REST APIs, Microservices, Cloud Architecture, Data Pipelines, DevOps, CI/CD, Containerization, Automation

Delivery & Process:
Agile/Scrum, Sprint Planning, Milestone Tracking, Release Management, Production Support, Customer Management, Cross-functional Collaboration

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