Solution Architect – Python

EPAM Systems; Bengaluru; On-site; INR 4,000,000 - 6,400,000; Full time

Job summary

EPAM Systems in Bengaluru is seeking a Solution Architect with deep Python and GenAI expertise to design enterprise-grade GenAI solutions for production use. You will lead architecture explorations, craft reusable frameworks and set standards for LLM-based applications.

You will collaborate across cross-functional teams, drive scalable microservices, RAG, and MLP workflows while guiding engineers and mentoring peers to deliver actionable GenAI outcomes for clients.

Qualifications

• 9–14 years of software development and architecture experience.
• Deep GenAI experience including RAG, Agents, and multi-agent setups.
• Production-grade Python development with microservices.

Responsibilities

• Architect GenAI systems including RAG frameworks and multi-agent configurations.
• Develop reusable accelerators and reference builds for delivery consistency.
• Lead technical discovery workshops and support engineering teams.
• Establish evaluation methodologies for LLM-based applications.
• Ensure scalable, maintainable system designs across teams.
• Build microservices-based architectures using modern frameworks.
• Incorporate cloud infrastructure across AWS, Azure, or GCP.
• Containerize and orchestrate with Docker and Kubernetes.
• Evaluate vector databases: Pinecone, Weaviate, Chroma.
• Deploy LLMOps and monitoring for production deployments.
• Manage prompts and RAG evaluation to improve accuracy.
• Mentor architecture team and promote knowledge sharing.
• Maintain production-ready Python code quality.
• Push ongoing architecture and scalability enhancements.

Skills

Python

Microservices design

FastAPI

LLMOps

RAG

LangGraph

LangChain

Production-ready code

English communication

Tools

Docker

Kubernetes

Redis

Elasticsearch

Kafka

Pinecone

Weaviate

Chroma

AWS

Azure

GCP

FastAPI

Job description

Our team is expanding, and we're bringing on a Solution Architect with deep specialization in Python and Generative AI to build and deliver enterprise-grade GenAI solutions ready for real-world production use. You'll be an integral part of our Solution Architecture group, spearheading technical exploration efforts, crafting reusable frameworks, and shaping standards for LLM-based applications. Submit your application to take part in forward-thinking GenAI initiatives and empower clients to achieve breakthrough outcomes.

Responsibilities

• Architect complete GenAI systems, including RAG frameworks, Agents, and Multi-Agent configurations, tailored for enterprise-level clients
• Develop reusable accelerators and reference builds to bring consistency to delivery approaches
• Facilitate technical discovery workshops while offering direct, practical support to engineering teams
• Establish evaluation methodologies and set standards for building large language model (LLM) applications
• Work alongside diverse teams to guarantee system designs that scale effectively and remain easy to maintain
• Build out microservices-based architectures leveraging established design patterns and contemporary frameworks
• Manage the incorporation of cloud infrastructure elements across platforms like AWS, Azure, or GCP
• Handle containerization and orchestration processes utilizing Docker and Kubernetes
• Assess and choose suitable vector database solutions, such as Pinecone, Weaviate, or Chroma, for GenAI use cases
• Deploy LLMOps methodologies and monitoring solutions to fine-tune production-level deployments
• Assist with prompt management and RAG evaluation processes to boost application precision
• Take part in mentoring efforts and knowledge exchange across the broader architecture team
• Maintain high standards of production-ready code quality within Python-based applications
• Push forward ongoing enhancements in system architecture and solution scalability

Requirements

• Between 9 and 14 years of experience in software development, with a strong foundation in solution architecture and system design
• Advanced Python development skills with a focus on writing production-ready code
• Skilled in microservices design, architectural patterns, FastAPI, Redis, Elasticsearch, and Kafka
• Substantial background building GenAI applications, covering Agents, MCP, RAG, Agentic RAG, and GraphRAG
• Strong familiarity with LangGraph, LangChain, and related orchestration tools
• Hands-on background in evaluating LLMs and RAG systems, along with managing prompts
• Demonstrated success in delivering scalable GenAI applications ready for production environments
• Working experience with cloud ecosystems such as AWS, Azure, or GCP
• Comfortable with containerization tools, namely Docker and Kubernetes
• Familiarity with vector database technologies, including Pinecone, Weaviate, or Chroma
• Solid grasp of LLMOps principles and associated monitoring solutions
• Strong leadership capabilities suited to directing engineering teams
• Capacity to thrive in client-facing settings while working collaboratively
• Solid English communication skills, both written and spoken, at B2 level or above

Nice to have

• Experience in conventional machine learning practices, including feature engineering, model training, and evaluation methods
• Familiarity with knowledge graphs along with fine-tuning approaches
• Previous background in consulting positions or client-facing capacities