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EPAM Systems

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Solution Architect – Python with GenAI

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Our growing organization needs a Solution Architect with expertise in Python and Generative AI to engineer and roll out enterprise-level GenAI solutions capable of operating reliably in production. Within our Solution Architecture team, you'll steer technical exploration projects, develop reusable building blocks, and contribute to shaping standards for LLM-powered applications. Submit your application now to join forward-looking GenAI initiatives and help clients realize meaningful, transformative outcomes.

Responsibilities

  • Develop end-to-end GenAI architecture solutions, covering RAG approaches, Agents, and Multi-Agent designs, tailored to large enterprise needs
  • Build reusable accelerator assets and reference solutions to create consistency across delivery
  • Head up technical discovery meetings and give practical, on-the-ground support to engineering teams
  • Establish evaluation frameworks and outline standards guiding the creation of LLM-based applications
  • Work with multiple teams to confirm that architectural approaches remain scalable and manageable over the long haul
  • Engineer microservices systems by drawing on recognized patterns and modern technology frameworks
  • Oversee integration efforts tied to cloud infrastructure across platforms such as AWS, Azure, or GCP
  • Handle container deployment and orchestration responsibilities via Docker and Kubernetes
  • Assess and determine fitting vector database technologies, like Pinecone, Weaviate, or Chroma, to power GenAI solutions
  • Roll out LLMOps techniques and monitoring systems to elevate the quality of production releases
  • Aid in prompt engineering work and RAG evaluation to strengthen application dependability
  • Take part in mentoring programs and share insights across the architecture community
  • Maintain rigorous coding practices for Python applications intended for production use
  • Guide ongoing efforts to enhance system architecture design and solution scalability

Requirements

  • Experience spanning 9 to 14 years in software development, with strong expertise in solution architecture and system design
  • Advanced Python capabilities focused on writing code fit for production environments
  • Skill set covering microservices architecture, design patterns, FastAPI, Redis, Elasticsearch, and Kafka
  • Deep hands-on experience creating GenAI applications, including Agents, MCP, RAG, Agentic RAG, and GraphRAG
  • Strong knowledge of LangGraph, LangChain, and other orchestration technologies
  • Practical background evaluating LLMs and RAG frameworks, along with handling prompt management tasks
  • Proven capability delivering GenAI applications that scale effectively in production
  • Direct experience with cloud environments, including AWS, Azure, or GCP
  • Familiarity with containerization approaches, particularly Docker and Kubernetes
  • Understanding of vector database platforms, such as Pinecone, Weaviate, or Chroma
  • Solid comprehension of LLMOps principles and the monitoring tools tied to them
  • Strong leadership abilities appropriate for directing engineering teams
  • Capability to work in client-facing scenarios while collaborating effectively with teams
  • Solid English language skills, both spoken and written, at a B2 level or higher

Nice to have

  • Experience with conventional machine learning techniques, including feature engineering, model training, and evaluation
  • Familiarity with knowledge graph principles and fine-tuning strategies
  • Previous exposure to consulting work or roles centered on direct client interaction

Benefits

Opportunity to work on technical challenges that may impact across geographies

Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications

Opportunity to share your ideas on international platforms

Sponsored Tech Talks & Hackathons

Unlimited access to LinkedIn learning solutions

Possibility to relocate to any EPAM office for short and long-term projects

Focused individual development

Benefit package:

  • Health benefits
  • Retirement benefits
  • Paid time off
  • Flexible benefits

Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)

Skills

See also

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