AI Software Engineer

About the role

Entrata India is seeking an AI Software Engineer to design, build, and maintain advanced large‑language‑model (LLM) and agentic workflows that power its AI‑driven property‑management platform. The role covers end‑to‑end development from model selection and prompt engineering to integration with AWS services, ensuring reliable, secure, and scalable AI capabilities for customers.

Responsibilities

• Develop, deploy, and sustain production‑grade LLM, agent, and retrieval workflows using structured orchestration patterns.
• Design and maintain agent graphs, state machines, routing logic, retries, fallbacks, and tool integrations.
• Engineer prompts and structured outputs, handling system, task, and tool instructions with guardrails.
• Manage short‑term and long‑term memory, conversation history, summarisation, and privacy boundaries.
• Select and configure models based on latency, cost, context length, and reliability requirements.
• Integrate AI components with AWS services such as Amazon Bedrock and AgentCore, linking to APIs, databases, and existing services.
• Build robust retrieval and grounding pipelines using chunking, embeddings, ranking, and metadata filtering.
• Create and run quantitative and qualitative evaluation suites to measure correctness, safety, latency, and regression.
• Diagnose and resolve unexpected agent behaviour through logs, traces, and observability tooling.
• Own AI projects from design through production, defining reusable libraries and patterns for the engineering team.
• Collaborate with product, design, data science, and engineering peers to translate ambiguous problems into reliable AI features.

Eligibility

• 1–4 years of software engineering experience, with at least 2 years focused on AI or data‑science technologies.
• Proficiency in Python and JavaScript/TypeScript, including strong Node.js skills.
• Hands‑on experience building and operating LLM or agentic systems in production.
• Deep understanding of prompting, tool calling, structured outputs, and memory management.
• Experience designing agent graphs, multi‑step workflows, and failure‑handling strategies.
• Familiarity with model evaluation, cost‑latency trade‑offs, and cloud AI services such as Amazon Bedrock.
• Knowledge of RAG techniques, vector databases, embeddings, and ranking mechanisms.
• Ability to create evaluation frameworks and use production data for diagnostics.
• Solid grasp of APIs, distributed services, containers, CI/CD pipelines, and observability practices.
• Strong communication, ownership, and collaborative skills.

Skills

• Python
• JavaScript / TypeScript
• Node.js
• Large Language Models (LLM) and agentic architectures
• Prompt engineering and structured output design
• Retrieval‑augmented generation (RAG) and vector databases
• AWS AI services (Amazon Bedrock, AgentCore)
• Model selection, configuration, and performance tuning
• CI/CD, containerisation, and cloud deployment
• Observability, logging, and debugging of AI systems