Solution Architect – Python with GenAI

Hybrid in India: Bengaluru, India: Hyderabad

Python.ML

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We're growing our team and looking to add a Solution Architect who specializes in Python and Generative AI, tasked with designing and delivering enterprise-scale GenAI solutions suited for live production environments. Joining our Solution Architecture unit, you'll take the lead on technical investigation work, build out reusable toolkits, and help establish guidelines for LLM-driven applications. Apply today to become part of innovative GenAI projects and help drive transformative results for our clients.

Responsibilities

Construct comprehensive GenAI architectures, encompassing RAG structures, Agents, and Multi-Agent setups, designed specifically for large enterprise clients
Create reusable accelerator tools and reference models to standardize how solutions get delivered
Run technical discovery workshops and provide hands-on assistance directly to engineering teams
Set up evaluation frameworks and establish guidelines governing the development of large language model (LLM) applications
Partner with varied teams to ensure system architectures are built to scale properly and stay maintainable over time
Design microservices architecture using proven patterns and up-to-date frameworks
Direct the integration of cloud infrastructure components spanning platforms such as AWS, Azure, or GCP
Take charge of containerization and orchestration tasks using Docker and Kubernetes
Weigh options and select appropriate vector database platforms, including Pinecone, Weaviate, or Chroma, to support GenAI initiatives
Apply LLMOps approaches and monitoring frameworks to improve production deployment outcomes
Contribute to prompt management efforts and RAG evaluation work to increase application accuracy
Engage in mentorship activities and share expertise throughout the wider architecture team
Uphold rigorous production-quality coding standards within Python-based applications
Champion continual improvements in system architecture and the scalability of solutions

Requirements

9 to 14 years of experience within software development, backed by a strong background in solution architecture and system design
Advanced-level Python programming ability with an emphasis on producing production-quality code
Proficiency spanning microservices architecture, design patterns, FastAPI, Redis, Elasticsearch, and Kafka
Considerable experience developing GenAI applications, including work with Agents, MCP, RAG, Agentic RAG, and GraphRAG
Thorough understanding of LangGraph, LangChain, and comparable orchestration technologies
Direct experience conducting LLM and RAG evaluations, plus managing prompt-related workflows
Solid history of successfully delivering scalable, production-ready GenAI applications
Practical exposure to cloud platforms, including AWS, Azure, or GCP
Working familiarity with containerization solutions such as Docker and Kubernetes
Knowledge of vector database technologies, including options like Pinecone, Weaviate, or Chroma
Clear understanding of LLMOps concepts and the tools used for monitoring
Proven leadership qualities capable of guiding and directing engineering teams
Ability to perform effectively in client-facing roles while collaborating across teams
Proficient English communication abilities, spoken and written, at a B2 level or higher

Nice to have

Exposure to classic machine learning approaches, such as feature engineering, model training, and performance evaluation
Knowledge of knowledge graph structures and fine-tuning methodologies
Background in consulting work or roles requiring direct client interaction