Solution Architect – Python

EPAM Systems; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

EPAM Systems in Hyderabad seeks an experienced Solution Architect to lead GenAI initiatives, architecting enterprise-grade GenAI solutions and scalable microservices. You will craft reusable frameworks, guide LLM-based applications, and collaborate with cross-functional teams to deliver production-ready GenAI platforms.

The role emphasizes hands-on Python development, architectural leadership, and client-facing delivery, with hands-on cloud and containerization expertise in AWS/Azure/GCP,

Qualifications

• 9–14 years of software development with solution architecture experience.
• Advanced Python production-ready coding skills.
• Experience building GenAI apps with RAG, Agents, and LLMs.
• Experience with cloud platforms AWS/Azure/GCP.

Responsibilities

• Architect GenAI systems including RAG frameworks and multi-agent configurations.
• Develop reusable accelerators and reference builds for delivery consistency.
• Lead discovery workshops and support engineering teams.
• Set standards for building production-ready LLM applications.
• Ensure scalable, maintainable system designs across teams.
• Implement Docker/Kubernetes based microservices architectures.
• Evaluate vector databases like Pinecone, Weaviate, or Chroma.
• Apply LLMOps practices to production deployments.
• Mentor the architecture team and ensure code quality.
• Collaborate with clients in a face-to-face or remote setting.
• Maintain strong English communication.

Skills

Python development

Microservices design

FastAPI

Redis

Elasticsearch

Kafka

LLMOps

LangGraph

LangChain

Docker

Kubernetes

Cloud: AWS/Azure/GCP

Client-facing

Leadership

English B2+

Tools

Docker

Kubernetes

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