Service Engineer
No of Opening 3
Job Location: Ahmedabad
Responsibilities for Service Engineer
· Customer Complaint Resolution.
· Solving the technical problems of the customers by calls, video call or remote diagnosis (team viewer).
· Establishing programs/seminar in the areas allocated for promotion of car scanner.
· Register the diagnosis tool and generate the ID PWs Diagnostic Tools & Equipments.
· Responsible for Trouble shooting of various faults arising. For example trouble shooting of AUDI, BMW, MAHINDRA, MERCEDECES etc.
· Provide technical training to our customers, engineers and co-ordinates.
· To visit field (workshop) for new diagnosis tool update and create report of the same.
· Preparing and submitting service and customer feedback reports (Daily report).
· Generate revenue from aftersales.
· Handling overall sales and aftersales equipment warranty claims.
Qualifications for Service Engineer
· Must be equivalent Degree or Diploma in Automobile.
· Must be fluent in English and Hindi.
· Additional language will be an advantage.
· Minimum of 2 to 3 years of experience in Automobile workshop.
· Knowledge of Excel and Power point presentation.
Salary & Perks:
· Salary 25000 to 35000 Per month plus insurance plus incentive
· Insurance facilities.
· Petrol allowances.
Age for Service engineer
24 years to 30 years

About M-KAT LAUNCH INDIA
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- Design end-to-end AI solution architectures, including:
- Generative AI and LLM-based systems
- Retrieval-Augmented Generation (RAG) pipelines
- Agentic and multi-agent workflows
- Define reference architectures and best practices for AI-enabled features within enterprise products.
- Ensure AI solutions integrate seamlessly with existing applications, data, and cloud architectures.
AI Integration & MCP Servers
- Design and implement Model Context Protocol (MCP) servers to securely expose tools, APIs, and data to AI agents.
- Define standards for tool interfaces, access control, auditing, and safety guardrails.
- Enable product teams to onboard AI tools and capabilities using reusable, scalable integration patterns.
Agentic AI & Workflow Enablement
- Architect AI-driven workflows that support collaboration between humans and AI agents.
- Design AI-to-AI (A2A) and AI-to-system interaction patterns.
- Ensure agent behaviors are deterministic, explainable, and aligned with enterprise requirements.
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- Build proofs-of-concept and production-ready implementations using Python and/or TypeScript.
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- Establish reusable frameworks, libraries, and CI/CD pipelines for AI development.
AI Governance, Quality & Safety
- Implement guardrails to minimize hallucinations, unsafe actions, and data leakage.
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- Ensure AI solutions comply with enterprise security, privacy, and governance standards.
Developer Enablement & Collaboration
- Partner with Product, Engineering, QE, Performance, and Security teams to deliver AI capabilities.
- Mentor teams on AI design patterns, tooling, and best practices.
- Contribute to internal AI communities through demos, documentation, and knowledge sharing.
Qualifications :
Required Qualifications
- Bachelor’s degree in computer science, Engineering, or a related technical field, or equivalent practical experience.
- Demonstrated expertise in cloud‑native system design, distributed architectures, and enterprise‑scale integrations.
- Proven ability to architect and implement AI-enabled systems, including integrating Large Language Models (LLMs) into production-grade software.
- Strong ownership of architectural decisions, technical direction, and solution delivery across complex, cross-functional initiatives.
- Hands-on experience applying security, observability, and automation best practices within enterprise environments.
- 6–10 years of experience in software architecture and distributed systems.
- 5+ years of experience building Generative AI or LLM-based solutions.
- Practical experience designing and implementing:
- Retrieval-Augmented Generation (RAG) architectures
- Agentic AI systems
- Tool-calling frameworks and AI integration layers
- Proficiency in Python and/or .Net/TypeScript/Node.js.
- Experience working with major cloud platforms such as Azure, AWS, or Google Cloud Platform (GCP).
Preferred Qualifications
- Experience with OpenAI, Azure OpenAI, Anthropic, or similar LLM platforms.
- Familiarity with Model Context Protocol (MCP) or equivalent AI tool-integration frameworks.
- Experience applying AI engineering practices beyond prototyping, including evaluation, reliability, and scalability considerations.
- Ability to translate ambiguous business problems into clear technical architecture and execution plans.
- History of influencing technical standards and mentoring senior engineers or architects.
- Experience with vector databases, embeddings, and retrieval optimisation.
- Experience building AI-enabled developer tooling and CI/CD pipelines.
- Prior experience in enterprise SaaS environments.
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- Identify the RCA (Root cause analysis) and the action items and document it in the internal note. This will help in breaking the issue into smaller parts and understand the cause for it. Guidelines for identification of RCA are present in the SOP
- Follow up with the owner with the result of RCA to identify the action items.
- Respond back to the employee with the best possible solution.
- Monitor the resolution for a day (if required) and then close the ticket.
- Quality check for every call will be done on a real time basis.
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Functional Area: Internet & Cloud Technologies
Role Category: Programming & Deployment
Role: Software Developer
Employment Type: Permanent Job, Full Time
Desired Experience: 2-4 years
Desired Qualifications: B.E. / B.Tech / M.Tech / MCA
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