Software Engineer (Agentic AI, LLM, Python | 5 to 8 Years)

Overview

Software Engineer focused on Agentic AI/LLM backend and data platforms, building scalable Python systems and production-ready models with performance and cost optimization.

What you'll do

• Align designs to overall architecture for backend, data, cloud, and AI platforms.
• Lead design of scalable Python backend systems and data pipelines.
• Drive architecture and development of complex Agentic AI/LLM systems using LangGraph.
• Define strategies for LLM performance, token, latency, and cost optimization.
• Establish standards for AI/RAG architecture, APIs, databases, and distributed systems.
• Drive AWS/cloud-native architecture using S3, SQS, SNS, Lambda, Docker, and Kubernetes.
• Lead complex technical and production issue resolution across teams.

What you'll need

• 5–10 years of hands-on experience in machine learning engineering, backend development, and applied AI.
• Deep experience with Agentic AI, LLM applications, LangGraph, and RAG architectures.
• Proven experience operationalizing deep learning and LLM models in production.
• Proven experience deploying LangGraph and multi-agent workloads with versioned prompts, runtime safeguards, and rollback strategy.
• Strong experience defining and implementing token, latency, throughput, and cost optimization strategies for LLM systems.
• Experience with LLM evaluation and observability tooling (e.g., LangSmith or equivalent).
• Expertise in ETL optimization (e.g., scheduling, partition pruning, caching, storage-format tuning).
• Strong expertise in Python, backend engineering, and distributed systems.