We are looking for an AI Backend Engineer with strong expertise in Python, AI/ML systems, large-scale data platforms, and enterprise AI deployments. This is a highly collaborative and client-facing role where you will work closely with business stakeholders, leadership teams, and technical users to design and implement AI-powered solutions that solve real-world enterprise challenges.
Responsibilities
- Design, develop, and deploy AI-powered backend systems for enterprise applications.
- Build and integrate solutions using modern LLM platforms such as OpenAI and Anthropic.
- Develop scalable AI pipelines and backend services using Python.
- Work with large-scale structured and unstructured datasets to generate actionable insights.
- Develop and optimize machine learning models and AI workflows for production environments.
- Collaborate with clients and cross-functional teams to understand business requirements and deliver impactful solutions.
- Contribute to MLOps practices, model deployment, monitoring, and lifecycle management.
- Work closely with Palantir Foundry and enterprise data ecosystems to drive business outcomes.
Requirements
- 3-7 years of experience in AI Engineering, Machine Learning, Data Science, or Backend Development.
- Strong hands-on experience with Python (Mandatory).
- Experience with AI/ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Experience building solutions using OpenAI, Anthropic, or similar LLM platforms.
- Strong understanding of machine learning model development and deployment.
- Experience working with large and complex datasets.
- Knowledge of MLOps, production deployments, and model lifecycle management.
- Strong communication skills and ability to work directly with global stakeholders and enterprise clients.
Preferred Skills
- Hands-on experience with Palantir Foundry (Highly Preferred).
- Experience with Databricks, Snowflake, or similar data platforms.
- Exposure to Agentic AI, Generative AI, and Decision Intelligence systems.
- Experience with AWS, Azure, or GCP cloud platforms.
- Background in Data Engineering or distributed systems.
- Experience in client-facing or forward-deployed engineering roles.