Artificial Intelligence Developer

Role & responsibilities

Strong proficiency in Python for backend and AI development.

• Agentic Frameworks: Experience with LangGraph, AutoGen, CrewAI, or similar frameworks.
• Cloud Platforms: Proficiency in one of the cloud platfrom and associated GenAI services AWS (Bedrock, Lambda, Cognito), Azure, or GCP.
• Evaluation & Testing: Experience in agent evaluation, scoring functions, and debugging tools.
• Proven experience in designing and building AI/ML systems, including GenAI agents, RAG pipelines, and LLM orchestration.
• Expertise in AWS (Bedrock, SageMaker, Inferentia) or Azure OpenAI, or Google Vertex AI.
• Containerization & Deployment: Familiarity with Docker, Kubernetes, and CI/CD pipelines for scalable deployment.
• Understanding of GDPR, CCPA, and responsible AI principles including bias mitigation and explainability.
• Experience integrating AI systems with MCP servers, APIs, and enterprise data sources.
• Data Engineering: Experience with vector databases, graph databases, and ingestion pipelines.

• Build and deploy agentic applications using LLMs and agentic frameworks.

• Develop MCP-compatible servers and integrate agents with enterprise systems (e.g., ERP, CRM, HCM).

• Fine-tune models and optimize agent workflows for performance and reliability.

• Design agent evaluation pipelines and scoring logic.

• Conduct functional, regression, and adversarial testing.

Preferred candidate profile