Senior AI Software Engineer – Agentic AI / LLM Systems

Role Overview

We are looking for a hands-on AI Software Engineer to design, build, and deploy agentic AI systems powered by large language models (LLMs).

This is a deeply technical individual contributor role focused on building production-grade AI systems, not architecture-only or leadership positions.

You will work on developing multi-agent workflows, intelligent automation systems, and scalable LLM platforms to enhance production operations and decision-making.

Key Responsibilities:

• Design and develop agentic AI systems using LLMs, tool-calling, and orchestration frameworks
• Build and deploy multi-agent workflows (planning, reasoning, execution loops)
• Develop backend services and APIs to support AI-driven applications
• Implement RAG pipelines and retrieval systems for enterprise-scale use cases
• Integrate AI systems with observability, monitoring, and operational workflows
• Deploy and scale systems using cloud infrastructure, containers, and orchestration tools
• Ensure reliability, evaluation, and governance of LLM-based systems
• Collaborate with engineering teams to deliver production-ready AI solutions

Required Qualifications

• 7–12 years of experience in software engineering, AI/ML engineering, or backend systems
• Strong programming skills in Python (required)
• Proven experience building production-grade systems (APIs, microservices, distributed systems)
• Hands-on experience with LLMs and GenAI systems

MUST-HAVE SKILLS (CRITICAL)

• Experience building agent-based AI systems
• Multi-agent orchestration
• Tool usage / function calling
• Planning / reasoning workflows
• Hands-on experience with frameworks such as:
  • LangGraph, LangChain, AutoGen, CrewAI (or similar)
• Experience building and deploying:
  • RAG pipelines
  • LLM-powered applications
• Strong backend engineering experience:
  • REST APIs (FastAPI, Flask, etc.)
  • Microservices / distributed systems
• Experience with deployment and scaling:
  • Docker, Kubernetes
  • Cloud platforms (AWS, GCP, or Azure)

Preferred Qualifications

• Experience with LLM evaluation frameworks (Ragas, Langfuse, etc.)
• Experience building production agent systems at scale
• Familiarity with observability, monitoring, and reliability engineering
• Experience in financial services or enterprise environments

Not a Fit If

• Primarily focused on architecture, strategy, or leadership roles
• Limited hands-on coding or system development
• Experience limited to POCs or basic chatbot implementations
• Pure data science or research-focused background

Key Traits

• Strong engineering mindset (builder first)
• Ability to design and implement end-to-end systems
• Comfortable working in production environments
• High ownership and problem-solving ability