AI Software Architect / Senior AI Engineer (LLM & Agentic Systems)

Zoho; Hyderabad; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

BuildxPartners in Hyderabad, India, seeks an AI Software Architect / Senior AI Engineer to design and operate production-grade AI systems powered by LLMs. You will own end-to-end architecture, including retrieval-augmented generation, agentic workflows, tool calling, and observability in production environments.

Candidates bring 10+ years in software engineering with at least 5 years in LLM-based solutions, strong Python, Docker, Kubernetes, and cloud skills.

Qualifications

• Master's degree in Computer Science, AI, or related field.
• 10+ years of software engineering experience with at least 5 years focused on LLM-based solutions and generative AI systems.
• Proven experience deploying complex production-grade AI applications using Large Language Models.
• Hands-on experience with AI orchestration frameworks and observability tools.

Responsibilities

• Own the architecture of AI-powered services and their integration with backend, mobile, and web applications.
• Design, build, and maintain production-grade LLM applications using modern AI frameworks and orchestration platforms.
• Lead architectural design reviews and drive decisions across AI services, data pipelines, and cloud infrastructure.
• Architect agentic workflows involving tool use, function calling, multi-agent systems, planning, memory management, and reasoning chains.
• Establish evaluation frameworks to measure AI quality, reliability, latency, cost, and business impact.
• Implement AI observability and monitoring using Langfuse, LangSmith, OpenTelemetry, and related tooling.
• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases, embeddings, document pipelines, and retrieval optimization techniques.
• Collaborate with software engineers, data scientists, product managers, and domain experts to translate requirements into AI solutions.
• Optimize prompts, retrieval strategies, model selection, and system architecture for accuracy, reliability, performance, and cost efficiency.
• Design scalable APIs and services to expose AI capabilities across internal and external applications.
• Define AI engineering standards, best practices, and governance processes across the organization.
• Provide technical leadership and mentorship to engineers working on AI initiatives.
• Leverage cloud platforms such as Google Cloud Platform (GCP) to deploy and scale AI services.
• Document AI architectures, workflows, evaluation methodologies, and operational procedures.

Skills

LLM architectures

Python

Docker

Kubernetes

APIs design

LangChain

RAG

Vector databases

Observability tooling

Education

Master's degree in Computer Science, AI, or related field

Tools

LangGraph

LangChain

LlamaIndex

CrewAI

Docker

Kubernetes

PostgreSQL

Job description

AI Software Architect / Senior AI Engineer (LLM & Agentic Systems)

Seri Lingampally, India | Posted on 23/09/2026

BuildxPartners is a global talent solutions firm delivering end-to-end recruitment and workforce solutions across industries and geographies.

→ BuildxAlpha – Executive & Leadership Search Focused on C-suite, board, and global executive hiring.

→ BuildxSigma – Comprehensive Talent Across Levels Covering junior, mid-level, and senior professionals.

→ BuildxGCC – Global Capability Center Solutions Specializing in Build, Operate, Transfer (BOT) model for Global Capability Centers, GCC supports companies in setting up, scaling, and transferring GCCs.

Job Description

Position Overview

We are looking for an AI Software Architect / Senior AI Engineer who is a self-starter and thrives on designing and delivering production-grade AI solutions powered by Large Language Models (LLMs). This role requires deep expertise in architecting, building, and operating complex AI systems, including Retrieval-Augmented Generation (RAG), agentic workflows, tool calling, evaluation frameworks, and observability platforms.

The ideal candidate combines strong software engineering fundamentals with demonstrated experience delivering real-world AI products. Beyond experimentation, this individual must be capable of designing scalable, reliable, and cost-effective LLM-powered solutions that operate successfully in production environments. They should possess a strong understanding of modern AI architecture patterns, prompt engineering, retrieval systems, agent orchestration, and AI observability.

Key Responsibilities

• Own the architecture of AI-powered services and their integration with backend, mobile, and web applications.
• Design, build, and maintain production-grade LLM applications using modern AI frameworks and orchestration platforms.
• Lead technical design reviews and drive architectural decisions across AI services, backend systems, data pipelines, and cloud infrastructure.
• Architect agentic workflows involving tool use, function calling, multi-agent systems, planning, memory management, and reasoning chains.
• Establish evaluation frameworks to measure AI quality, reliability, latency, cost, and business impact.
• Implement AI observability and monitoring using platforms such as Langfuse, LangSmith, OpenTelemetry, and related tooling.
• Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases, embeddings, document pipelines, and retrieval optimization techniques.
• Collaborate with software engineers, data scientists, product managers, and domain experts to translate business requirements into AI solutions.
• Optimize prompts, retrieval strategies, model selection, and system architecture for accuracy, reliability, performance, and cost efficiency.
• Design scalable APIs and services to expose AI capabilities across internal and external applications.
• Define AI engineering standards, best practices, and governance processes across the organization.
• Provide technical leadership and mentorship to engineers working on AI initiatives.
• Leverage cloud platforms such as Google Cloud Platform (GCP) to deploy and scale AI services.
• Document AI architectures, workflows, evaluation methodologies, and operational procedures.

Qualifications

• Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or related field.
• 10+ years of software engineering experience with at least 5 years focused on LLM-based solutions and generative AI systems.
• Demonstrated experience designing and deploying complex production-grade AI applications using Large Language Models.
• Extensive experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or equivalent technologies.
• Hands-on experience implementing AI observability and evaluation frameworks using Langfuse, LangSmith, or similar platforms.
• Proven expertise with Retrieval-Augmented Generation (RAG) architectures and vector database technologies.
• Strong understanding of modern LLM architectures, prompting strategies, context management, embeddings, and retrieval techniques.
• Strong Python development experience and software engineering fundamentals.
• Experience designing scalable APIs and cloud-native architectures.
• Ability to evaluate architectural trade-offs involving model performance, latency, reliability, maintainability, and cost.
• Experience deploying AI solutions in production environments using Docker, Kubernetes, and cloud platforms.
• Strong understanding of structured and unstructured data processing pipelines.
• Familiarity with modern database technologies including PostgreSQL, vector databases, and document stores.
• Excellent communication, leadership, and mentoring skills and ability to collaborate effectively with cross-functional teams.

Preferred Skills

• Experience building agentic systems involving tool use, planning, memory, and multi-agent orchestration and skills.
• Experience with model evaluation, benchmarking, AI testing frameworks, and automated quality assessment.
• Experience working with multiple commercial and open-source models including OpenAI, Anthropic, Gemini, Llama, and Mistral.
• Familiarity with fine-tuning, synthetic data generation, and model optimization techniques.
• Familiarity with developing and training machine learning models.
• Experience supporting AI products in regulated, privacy-sensitive, or high-availability environments.
• Experience integrating AI capabilities into mobile and web applications.
• Familiarity with modern software delivery practices including DevOps, CI/CD, and Agile development methodologies.