Mercedes-Benz Group AG

AI Engineer- AI Native Engineering

Mercedes-Benz Group AG  •  Bengaluru, IN (Onsite)  •  1 day ago
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Job Description

Tätigkeitsbereich:IT/Telekommunikation

Fachabteilung:WH Simulation

Gesellschaft:Mercedes-Benz Research and Development India Private Limited

Standort:Mercedes-Benz Research and Development India Private Limited, Bangalore

Startdatum:01.12.2026

Veröffentlichungsdatum:11.11.2026

Stellennummer:MER0004AAR

Arbeitszeit:Vollzeit

Bewerben

Aufgaben

Description - ExternalJob Description: AI Engineer (1-4 Years Overall Experience)

Location: Bengaluru

Employment Type: Full-Time

Role Purpose

The AI Engineer will design, develop and integrate AI-enabled capabilities into enterprise and manufacturing applications. The role will focus on Generative AI, intelligent automation, data integration and AI-assisted software engineering while building strong foundations in production-grade AI engineering.

The engineer will work with senior engineers and architects to convert manufacturing and business use cases into scalable AI solutions.

Key Responsibilities1. Generative AI & Agentic Solutions

  • Develop applications using LLMs and Generative AI.
  • Build RAG-based solutions using enterprise documents and structured/unstructured data.
  • Develop AI agents and tool-based workflows for engineering and business processes.
  • Implement prompt engineering, structured outputs and function/tool calling.
  • Evaluate AI responses for accuracy, relevance and reliability.
  1. AI Application Engineering
  • Develop APIs and backend services using Python and FastAPI.
  • Integrate AI capabilities into existing enterprise applications.
  • Build reusable AI services/components rather than standalone prototypes.
  • Develop proof-of-concepts and mature them toward production solutions.
  • Write clean, modular and testable code.
  1. Data & Knowledge Integration
  • Connect AI solutions with enterprise databases, APIs, documents and engineering systems.
  • Implement document ingestion, chunking, embedding and retrieval pipelines.
  • Work with SQL, REST APIs, JSON and structured/unstructured datasets.
  • Exposure to vector databases/search technologies such as Azure AI Search, PostgreSQL/pgvector or equivalent.
  1. AI-Native Software Engineering
  • Use AI coding assistants effectively across development, testing and documentation.
  • Build automated unit and integration tests.
  • Participate in code reviews and engineering quality practices.
  • Work with Git, CI/CD, containers and DevSecOps pipelines.
  • Contribute to reusable engineering accelerators and automation.
  1. Manufacturing AI Use Cases

Work with domain experts to develop solutions such as:

  • Engineering knowledge assistants
  • Manufacturing/planning copilots
  • Intelligent document processing
  • Automated engineering workflows
  • Semantic enterprise search
  • AI-assisted validation and testing
  • Data-driven recommendations
  • Agent-based process automation

Required Skills

Must-have

  • Bachelor's/Master's degree in Computer Science, AI, Data Science, Information Technology or related engineering discipline
  • Strong programming fundamentals in Python
  • Understanding of REST APIs and backend application development
  • Fundamentals of Generative AI and LLMs
  • Understanding of RAG, embeddings and vector search
  • Working knowledge of SQL and data handling
  • Git and modern software-development practices
  • Strong analytical and problem-solving skills

Good-to-have

  • Azure AI / cloud services
  • FastAPI
  • Azure OpenAI or equivalent LLM platforms
  • Azure AI Search
  • LangChain / Semantic Kernel or similar orchestration frameworks
  • Docker / Kubernetes
  • CI/CD and DevSecOps
  • React/Angular knowledge
  • ML/MLflow/MLOps fundamentals
  • Knowledge graphs
  • Agentic AI / multi-agent concepts

Qualifikationen

Description - ExternalJob Description: AI Engineer (1-4 Years Overall Experience)

Location: Bengaluru

Employment Type: Full-Time

Role Purpose

The AI Engineer will design, develop and integrate AI-enabled capabilities into enterprise and manufacturing applications. The role will focus on Generative AI, intelligent automation, data integration and AI-assisted software engineering while building strong foundations in production-grade AI engineering.

The engineer will work with senior engineers and architects to convert manufacturing and business use cases into scalable AI solutions.

Key Responsibilities1. Generative AI & Agentic Solutions

  • Develop applications using LLMs and Generative AI.
  • Build RAG-based solutions using enterprise documents and structured/unstructured data.
  • Develop AI agents and tool-based workflows for engineering and business processes.
  • Implement prompt engineering, structured outputs and function/tool calling.
  • Evaluate AI responses for accuracy, relevance and reliability.
  1. AI Application Engineering
  • Develop APIs and backend services using Python and FastAPI.
  • Integrate AI capabilities into existing enterprise applications.
  • Build reusable AI services/components rather than standalone prototypes.
  • Develop proof-of-concepts and mature them toward production solutions.
  • Write clean, modular and testable code.
  1. Data & Knowledge Integration
  • Connect AI solutions with enterprise databases, APIs, documents and engineering systems.
  • Implement document ingestion, chunking, embedding and retrieval pipelines.
  • Work with SQL, REST APIs, JSON and structured/unstructured datasets.
  • Exposure to vector databases/search technologies such as Azure AI Search, PostgreSQL/pgvector or equivalent.
  1. AI-Native Software Engineering
  • Use AI coding assistants effectively across development, testing and documentation.
  • Build automated unit and integration tests.
  • Participate in code reviews and engineering quality practices.
  • Work with Git, CI/CD, containers and DevSecOps pipelines.
  • Contribute to reusable engineering accelerators and automation.
  1. Manufacturing AI Use Cases

Work with domain experts to develop solutions such as:

  • Engineering knowledge assistants
  • Manufacturing/planning copilots
  • Intelligent document processing
  • Automated engineering workflows
  • Semantic enterprise search
  • AI-assisted validation and testing
  • Data-driven recommendations
  • Agent-based process automation

Required Skills

Must-have

  • Bachelor's/Master's degree in Computer Science, AI, Data Science, Information Technology or related engineering discipline
  • Strong programming fundamentals in Python
  • Understanding of REST APIs and backend application development
  • Fundamentals of Generative AI and LLMs
  • Understanding of RAG, embeddings and vector search
  • Working knowledge of SQL and data handling
  • Git and modern software-development practices
  • Strong analytical and problem-solving skills

Good-to-have

  • Azure AI / cloud services
  • FastAPI
  • Azure OpenAI or equivalent LLM platforms
  • Azure AI Search
  • LangChain / Semantic Kernel or similar orchestration frameworks
  • Docker / Kubernetes
  • CI/CD and DevSecOps
  • React/Angular knowledge
  • ML/MLflow/MLOps fundamentals
  • Knowledge graphs
  • Agentic AI / multi-agent concepts

Benefits

Mit­arbeiter­rabatte möglich

Gesund­heits­maß­nahmen

Mit­arbeiter­handy möglich

Essens­zulagen

Betrieb­liche Alters­ver­sorgung

Hybrides Arbeiten möglich

Mobilitäts­angebote

Mit­arbeiter Events

Coaching

Flexible Arbeits­zeit möglich

Park­platz

Betriebs­arzt

Gute An­bindung

Barriere­frei­heit

Kinder­betreuung

Kantine, Café

KontaktMercedes-Benz Research and Development India Private Limited

Brigade Tech Gardens, Katha No. 119560037 BengaluruDetails zum Standort

Jacob Cyril E-Mail: jacob.cyril@mercedes-benz.com

Bewerben

Mercedes-Benz Group AG

About Mercedes-Benz Group AG

Learn more about Mercedes-Benz, its products, innovations and our world!

Data privacy: mb4.me/provider

Imprint:

Mercedes-Benz AG

Mercedesstraße 120

D-70372 Stuttgart

Deutschland

Tel.: +49 7 11 17-0

E-Mail: dialog.mb@mercedes-benz.com

Vertreten durch den Vorstand:

Ola Källenius (Vorsitzender), Jörg Burzer, Renata Jungo Brüngger, Sabine Kohleisen, Harald Wilhelm, Markus Schäfer, Britta Seeger

Vorsitzender des Aufsichtsrats: Bernd Pischetsrieder

Handelsregister beim Amtsgericht Stuttgart, Nr. HRB 762873

Umsatzsteueridentifikationsnummer: DE321281763

Industry
Automotive & Mobility
Company Size
1,001-5,000 employees
Headquarters
Stuttgart, DE
Year Founded
Unknown
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