Description

Key Responsibilities

Design, develop, and deploy scalable AI and Generative AI applications in production environments.

Build and maintain LLM-powered solutions using modern AI platforms and frameworks.

Develop Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge sources.

Implement Agentic AI workflows using frameworks such as LangChain and LangGraph.

Create and integrate RESTful APIs to enable AI capabilities across business applications.

Collaborate with cross-functional teams to gather requirements and deliver AI-driven solutions.

Optimize AI applications for performance, scalability, reliability, and cost efficiency.

Conduct prompt engineering, model evaluation, testing, and continuous improvement of AI systems.

Deploy and manage applications using containerization and orchestration technologies such as Docker and Kubernetes.

Support MLOps practices including model deployment, monitoring, and lifecycle management.

Stay current with emerging AI technologies and contribute to innovation initiatives.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.

7+ years of software engineering experience with a strong development background.

3+ years of hands-on experience building and deploying AI/ML or Generative AI solutions.

Strong proficiency in Python and modern software development practices.

Experience developing AI applications using:

OpenAI

Azure AI Services

AWS Bedrock

LangChain

LangGraph

Vector Databases (e.g., Pinecone, Chroma, Weaviate, FAISS)

Experience building and consuming REST APIs.

Hands-on experience with Docker and Kubernetes.

Knowledge of cloud platforms such as Azure and AWS.

Experience implementing RAG architectures and AI agent frameworks.

Strong analytical, troubleshooting, and problem-solving skills.

Excellent communication and collaboration abilities.

Preferred Qualifications

Experience working within automotive, manufacturing, or industrial environments.

Knowledge of Industry 4.0 initiatives and enterprise digital transformation programs.

Experience with MLOps, CI/CD pipelines, and AI application monitoring.

Familiarity with AI governance and responsible AI practices.

Cloud or AI-related certifications.

Required Skills

Generative AI

Large Language Models (LLMs)

Retrieval-Augmented Generation (RAG)

Agentic AI

Python

OpenAI

Azure AI

AWS Bedrock

LangChain

LangGraph

Vector Databases

REST APIs

Docker

Kubernetes

Cloud Technologies (Azure/AWS)

MLOps

Prompt Engineering

AI Application Development

Key Skills

Education

Bachelor's degree