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

Quess IT Solutions; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Quess IT Solutions seeks an experienced AI/ML architect with a strong background in LLM solutions and production deployments. You will lead design of agentic workflows, RAG architectures, and vector DB strategies, while shaping cloud-native APIs and observability practices.

Responsibilities include guiding multi-disciplinary teams, ensuring robust scalability, and integrating AI across mobile and web interfaces with CI/CD discipline.

Qualifications

• 10+ years of software engineering experience.
• 5+ years focused on LLM/Generative AI solutions.
• Strong Python development expertise.
• Experience deploying LLM applications in production.
• Hands-on with LangGraph/LangChain/LlamaIndex/CrewAI.
• Designing agentic workflows and orchestration.
• Implementation of RAG architectures and vector databases.
• Observability for AI systems (Langfuse/LangSmith/OpenTelemetry).
• API and cloud-native architecture design.
• CI/CD, DevOps, and Agile practices.

Skills

Software engineering

LLM / Generative AI

Python development

LLM deployment

LangChain experience

Workflow orchestration

RAG architecture

Vector DB

AI observability

API design

Architecture leadership

Tools

LangChain

LlamaIndex

CrewAI

Docker

Kubernetes

GCP

PostgreSQL

Job description

10+ years software engineering experience

• 5+ years focused on LLM/Generative AI solutions
• Strong Python development expertise
• Production deployment of LLM applications
• LangGraph / LangChain / LlamaIndex / CrewAI experience
• Agentic workflow design and orchestration
• RAG architecture implementation
• Vector database expertise
• AI observability (Langfuse, LangSmith, OpenTelemetry)
• API and cloud-native architecture design
• Docker and Kubernetes experience
• Google Cloud Platform (GCP) exposure
• Database expertise (PostgreSQL, Vector DBs)
• Strong architecture and leadership capability

Preferred Requirements

• Multi-agent systems
• Tool calling and reasoning chains
• Model benchmarking and evaluation frameworks
• OpenAI, Anthropic, Gemini, Llama, Mistral experience
• Fine-tuning and synthetic data generation
• Machine Learning model development
• AI systems in regulated environments
• Mobile and web AI integrations
• CI/CD, DevOps, Agile methodology experience