Sr. Python: Agent Development

job Descrption : Sr. Python: Agent Development

Positions:5 Contract

Experience5 – 8 Years

Role Overview:

This role is for an experienced and high-caliber engineer with strong proficiency in Python and hands-on expertise integrating Large Language Models (LLMs) into production systems. This individual contributor (IC) role focuses on designing robust backend services and orchestrating LLM workflows.

Please note: this is a software engineering role, not one in data annotation, data science, or analytics.

What does day-to-day look like:

• Designing and implementing production-grade APIs and backend services in Python
• Building and maintaining LLM-powered systems, including agent frameworks and orchestration using tools like LangChain and LangGraph
• Efficiently integrating LLM calls into backend workflows
• Collaborating across functions to develop reliable, maintainable systems

Requirements:

• 5+ years of experience as a backend or full-stack engineer with a strong backend focus
• Advanced proficiency in Python
• Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar)
• Background in machine learning engineering is a strong plus
• Solid understanding of service architecture and production deployment workflows

Perks of Freelancing With Us:

• Work in a fully remote environment.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.
• Potential for contract extension based on performance and project needs.

Offer Details:

• Commitments Required: Full time 8 hours per day with a 4-hour overlap with PST
• Employment type : Contractor position (no medical/paid leave)
• Duration of contract : 3 month; [expected start date is next week]
• Location : India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Mexico

Evaluation Process (approximately 75 mins) :

• Two rounds of interviews (60 min technical + 30 min technical & cultural discussion

Job Type: Full-time

Pay: ₹200,000.00 - ₹2,500,000.00 per year

Schedule:

• Day shift

Work Location: In person