AI Engineer- AI Native Engineering

Daimler AG (Canada)

Bengaluru

On-site

INR 1,500,000 - 2,300,000

Full time

36 hours ago

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Job summary

Mercedes-Benz Research and Development India Private Limited in Bengaluru is seeking an AI Engineer to design, develop and integrate AI-enabled capabilities into enterprise and manufacturing applications. The role emphasizes Generative AI, intelligent automation, data integration and production-grade AI engineering.

You will collaborate with senior engineers to turn manufacturing and business use cases into scalable AI solutions, build reusable AI services, and ensure code quality through tests

Qualifications

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.

Responsibilities

Develop AI-enabled capabilities into enterprise and manufacturing applications focusing on Generative AI, intelligent automation, data integration and production-grade AI engineering.
Build APIs and backend services using Python and FastAPI and integrate AI capabilities into existing enterprise applications.
Connect AI solutions with enterprise databases, APIs, documents and engineering systems; implement document ingestion, embedding and retrieval pipelines.
Use AI coding assistants effectively across development, testing and documentation; build automated unit and integration tests and participate in code reviews.
Work with Git, CI/CD, containers and DevSecOps pipelines; contribute to reusable accelerators and automation.
Explore manufacturing AI use cases such as engineering knowledge assistants, coparticipation in planning and data-driven recommendations.

Skills

Python

REST APIs

Generative AI & LLMs

RAG

Vector search

SQL

Git

Software development practices

Problem solving

Education

Bachelor's/Master's degree in Computer Science, AI, Data Science, IT or related engineering

Tools

FastAPI

LangChain / Semantic Kernel

CI/CD

DevSecOps

React/Angular

Job description

Description

Description - External

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 Responsibilities

1. 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.

2. 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.

3. 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.

4. 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.

5. Manufacturing AI Use Cases

Work with domain experts to develop solutions such as:

Engineering knowledge assistants
Manufacturing/planning copilots
Automated engineering workflowsSemantic 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

FastAPI
LangChain / Semantic Kernel or similar orchestration frameworks
CI/CD and DevSecOps
React/Angular knowledge
Knowledge graphs
Agentic AI / multi-agent concepts