Solution Architect – Python

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

Job summary

EPAM Systems in Hyderabad is seeking a Solution Architect focused on Python and GenAI to design and deliver enterprise-grade GenAI solutions that run in live production. You will lead technical discovery, build reusable components, and define standards for LLM-enabled applications, collaborating with cross-functional teams to ensure scalable, reliable architectures.

You will mentor engineers, enforce production-grade Python practices, and work across AWS/Azure/GCP, Docker/Kubernetes, and vector

Qualifications

• 9 to 14 years in software development with solution architecture experience.

Responsibilities

• Design full-scale GenAI architecture solutions, including RAG models, Agents, and Multi-Agent frameworks.
• Produce reusable accelerator components and reference architectures to bring uniformity to solution delivery.
• Lead technical discovery sessions and deliver direct, practical support to engineering teams.
• Build evaluation frameworks and define standards that shape how LLM applications are developed.
• Collaborate with a range of teams to ensure architectural designs scale appropriately and remain sustainable long-term.
• Develop microservices-based systems by applying established patterns and current-generation frameworks.
• Guide the integration of cloud infrastructure across environments like AWS, Azure, or GCP.
• Manage container-based deployment and orchestration through Docker and Kubernetes.
• Evaluate and pick vector database options like Pinecone, Weaviate, or Chroma.
• Implement LLMOps strategies and monitoring tools to strengthen production rollouts.
• Support prompt engineering and RAG evaluation activities for reliability.
• Mentor initiatives and share knowledge across the architecture function.
• Enforce strong coding standards for production-level Python development.
• Lead efforts toward ongoing refinement of system architecture and scalability.

Skills

Python production-grade

Solution architecture

Microservices design

FastAPI

Redis

Elasticsearch

Kafka

LangGraph/LangChain

LLMOps

Team leadership

Client-facing

Cloud platforms

Docker

Kubernetes

Vector databases

Tools

Docker

Kubernetes

Pinecone

Weaviate

Chroma

Job description

Our expanding team is on the lookout for a Solution Architect focused on Python and Generative AI, responsible for engineering and delivering enterprise-caliber GenAI solutions built to perform in live production settings. As a member of our Solution Architecture team, you'll direct technical research initiatives, produce reusable tools, and help define standards for applications built around LLMs.

Responsibilities

• Design full-scale GenAI architecture solutions, including RAG models, Agents, and Multi-Agent frameworks, built for large-scale enterprise use
• Produce reusable accelerator components and reference architectures to bring uniformity to solution delivery
• Lead technical discovery sessions and deliver direct, practical support to engineering teams
• Build evaluation frameworks and define standards that shape how LLM applications are developed
• Collaborate with a range of teams to ensure architectural designs scale appropriately and remain sustainable long-term
• Develop microservices-based systems by applying established patterns and current-generation frameworks
• Guide the integration of cloud infrastructure elements across environments like AWS, Azure, or GCP
• Manage container-based deployment and orchestration efforts through Docker and Kubernetes
• Evaluate and pick suitable vector database options, such as Pinecone, Weaviate, or Chroma, for supporting GenAI projects
• Implement LLMOps strategies and monitoring tools to strengthen the quality of production rollouts
• Support prompt engineering and RAG evaluation activities aimed at improving application reliability
• Participate in mentoring initiatives and contribute knowledge across the architecture function
• Enforce strong coding standards for production-level Python development
• Lead efforts toward ongoing refinement of system architecture and solution scalability

Requirements

• A range of 9 to 14 years working in software development, with solid grounding in solution architecture and system design
• Expert-level Python skills geared toward delivering code suitable for production
• Capability across microservices design, architectural patterns, FastAPI, Redis, Elasticsearch, and Kafka
• Extensive hands-on background in GenAI application development, spanning Agents, MCP, RAG, Agentic RAG, and GraphRAG
• Deep familiarity with LangGraph, LangChain, and similar orchestration platforms
• Applied experience assessing LLMs and RAG systems while overseeing prompt management
• Established success delivering GenAI applications that scale well in production settings
• Hands-on background using cloud platforms like AWS, Azure, or GCP
• Comfort working with containerization technologies, specifically Docker and Kubernetes
• Awareness of vector database solutions, including Pinecone, Weaviate, or Chroma
• Firm grasp of LLMOps fundamentals and the monitoring tools that support them
• Demonstrated leadership skill suited for steering engineering teams
• Comfortable operating in client-facing capacities while maintaining strong team collaboration
• Strong English skills, covering both writing and speaking, at B2 level or above

Nice to have

• Background in traditional machine learning work, covering feature engineering, model training, and evaluation practices
• Understanding of knowledge graph concepts along with fine-tuning techniques
• Prior experience in consulting roles or positions involving direct client engagement