AI Engineer

Position Summary :

We are seeking an innovative AI Engineer to design, develop, test, and deploy AI-powered solutions that drive business value through automation, advanced analytics, and intelligent applications.

The AI Engineer will collaborate with cross-functional teams to build and test scalable machine learning and generative AI solutions that enhance operational efficiency and improve customer experiences.

Key Responsibilities :

- Design, develop, test, and deploy AI/ML and Generative AI solutions to solve complex business problems.

- Build and optimize data pipelines to support AI model training and inference.

- Develop and integrate Large Language Model (LLM) applications, AI agents, and Retrieval-Augmented Generation (RAG) solutions.

- Create scalable APIs and AI services for enterprise applications.

- Test agentic solutions and validate outputs to ensure accuracy, reliability, and expected behavior.

- Collaborate with data engineers, software developers, and business stakeholders to translate requirements into AI solutions.

- Evaluate, fine-tune, and monitor AI models for accuracy, performance, and reliability.

- Implement MLOps best practices for model deployment, testing, monitoring, and lifecycle management.

- Ensure AI solutions comply with enterprise security, governance, and responsible AI standards.

- Stay current with emerging AI technologies and recommend innovative approaches.

Required Qualifications :

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

- Strong programming skills in Python and SQL.

- Experience with Large Language Models (OpenAI, Anthropic, Llama, etc.) and prompt engineering.

- Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.

- Experience with REST APIs, Git, and software development best practices.

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

Preferred Qualifications :

- Experience with Snowflake, Databricks, or modern data platforms.

- Knowledge of vector databases, semantic search, and RAG architectures.

- Experience with AI orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.

- Familiarity with Docker, Kubernetes, and CI/CD pipelines.

- Experience developing AI-powered analytics dashboards using Streamlit.

Success Measures :

- Deliver scalable AI solutions that improve business outcomes.

- Automate manual processes through AI-driven workflows.

- Improve model accuracy, performance, and reliability.

- Successfully test agentic workflows and validate outputs against expected results.

- Partner effectively with stakeholders to translate business needs into AI capabilities.

- Continuously evaluate and adopt emerging AI technologies to drive innovation.