Description

Key Responsibilities

Design, develop, and implement enterprise AI and Generative AI applications.

Build AI-powered solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and prompt engineering techniques.

Collaborate with business stakeholders, product teams, and technical leaders to translate business requirements into scalable AI solutions.

Develop and integrate APIs and AI services with enterprise platforms and applications.

Optimize AI models, workflows, and system performance for scalability, reliability, security, and cost efficiency.

Partner with AI Architects, Data Engineers, Software Engineers, and Product Owners to deliver production-ready solutions.

Evaluate emerging AI tools, frameworks, and cloud services to enhance business outcomes.

Contribute to engineering best practices, reusable AI components, technical documentation, and development standards.

Support AI proof-of-concepts, pilot programs, and innovation initiatives.

Stay current with advancements in Generative AI, Agentic AI, cloud technologies, and AI engineering methodologies.

Required Qualifications

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

4 to 7 years of software engineering experience, including hands-on AI/ML or Generative AI development.

Strong proficiency in Python.

Experience with:

OpenAI or Azure OpenAI

Azure AI Services or AWS Bedrock

LangChain and/or LangGraph

Large Language Models (LLMs)

Retrieval-Augmented Generation (RAG)

AI Agents and Prompt Engineering

Vector Databases

REST API development and integration

Docker and Kubernetes

Git and cloud-native development practices

Cloud platforms such as Microsoft Azure or AWS

Experience integrating AI solutions with enterprise systems and applications.

Understanding of AI security, governance, and responsible AI principles.

Strong analytical, problem-solving, and communication skills.

Ability to collaborate effectively with both technical teams and business stakeholders.

Preferred Qualifications

Experience building and deploying production-grade RAG solutions and AI agent frameworks.

Knowledge of MLOps, CI/CD pipelines, and AI deployment best practices.

Experience within automotive, manufacturing, or industrial environments.

Microsoft Azure, AWS, or AI-related certifications.

Familiarity with enterprise AI architecture and governance frameworks

Key Skills

Education

Bachelor's degree