Job Summary
This role is ideal for a hands-on AI professional who is passionate about building and deploying enterprise-scale Generative AI solutions.
The successful candidate will play a key role in designing, developing, and implementing AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and cloud-native technologies.
The ideal candidate combines strong software engineering expertise with practical experience delivering production-ready AI solutions that drive business value and innovation.
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
Rate:
Not specified
Location:
Remote
IR35 Status:
Outside
Remote Status:
Remote
Industry:
AI & Machine Learning
Seniority Level:
Senior