Artificial Intelligence Engineer

If you have a minimum of 5 years of experience in AI/ML development for startups, this job is 

for you. As an AI Developer, you’ll design, develop, and implement innovative AI-powered 

solutions that automate workflows, optimize decision-making, and enhance user experiences. 

You’ll work closely with internal teams and clients to identify opportunities for AI integration 

and turn complex challenges into intelligent, scalable solutions.

Required Skills & Experience

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related 

field.

• 5+ years of experience in AI/ML development or automation engineering for startups.

• Strong programming skills in Python and experience with ML frameworks like 

TensorFlow, PyTorch, or Scikit-learn.

• Experience with API development and third-party integration (REST, GraphQL, etc.).

• Solid understanding of Rack system, embedding, data processing, model deployment, 

and MLOps concepts.

• Experience with prompt engineering, LLM-based applications, or chatbot development is 

a big plus.

• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker).

• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience working with large language models (LLMs) and AI agents.

• Knowledge of data visualization and dashboarding tools (Streamlit, Power BI, etc.).

• Understanding of AI ethics, data governance, and security practices.

• Prior experience automating business processes like procurement, HR, or customer 

service is a plus.

Key Responsibilities

• Design, develop, and deploy AI/ML-based solutions for automation, analytics, and 

decision support.

• Build intelligent workflows and agents using tools such as LangChain, OpenAI APIs, n8n, 

or custom Python frameworks.

• Implement natural language processing (NLP) models for text understanding, chatbots, 

and content generation.

• Develop and maintain data pipelines for training, inference, and real-time analytics.

• Integrate AI models with web platforms, ERP, or CRM systems via APIs.

• Work with business teams to identify problems that can be solved with AI and translate 

them into technical requirements.

• Monitor and continuously improve model accuracy, performance, and reliability.

• Stay up to date with the latest AI technologies, frameworks, and best practices.