Software Architect I

Job Title: Principal Software Engineer - Platform, Search & AI

Experience

8+ Years

Location

India (Hybrid)

Job Type

Full-Time

Job Summary

We are seeking a Principal Software Engineer - Platform, Search & AI to lead the architecture and development of scalable search platforms, distributed backend systems, and AI-powered solutions. This is a high-impact technical leadership role where you will define engineering standards, drive platform strategy, and build next-generation search and GenAI capabilities on AWS.

The ideal candidate will have deep expertise in Python, OpenSearch/Elasticsearch, distributed systems, AWS, and Generative AI technologies, including LLMs, RAG pipelines, semantic search, and vector databases. You will mentor engineering teams, influence technical decisions, and ensure the delivery of highly scalable and reliable AI-driven platforms.

Key Responsibilities

Platform Architecture & Technical Leadership

• Define and drive the long-term technical vision and architectural roadmap for platform, search, and AI capabilities.
• Lead architecture discussions and provide technical guidance across multiple engineering teams.
• Design scalable, resilient, and secure distributed systems on AWS.
• Represent engineering in architecture reviews and technical governance discussions.
• Mentor senior engineers and promote engineering excellence across the organization.

Backend Development

• Design and develop scalable backend services and microservices using Python.
• Build highly available APIs supporting search and AI applications.
• Drive best practices for software design, coding standards, and system reliability.

Search Platform Engineering

• Architect and optimize enterprise search solutions using OpenSearch or Elasticsearch.
• Design efficient indexing strategies, search relevance models, and query optimization.
• Improve search performance, scalability, and operational reliability.
• Implement semantic and vector search capabilities.

Generative AI & Search Intelligence

• Design and develop AI-powered search applications using Large Language Models (LLMs).
• Build Retrieval-Augmented Generation (RAG) pipelines and embedding-based search solutions.
• Implement semantic search and vector database integrations.
• Develop AI evaluation frameworks for response quality, relevance, and regression testing.
• Drive adoption of enterprise AI best practices.

Quality Engineering

• Define search quality metrics including Precision, Recall, NDCG, and MRR.
• Establish AI evaluation methodologies for benchmarking and automated scoring.
• Build frameworks for search relevance validation and LLM response evaluation.
• Drive continuous improvements in AI and search quality.

Cloud & DevOps

• Design cloud-native solutions on AWS.
• Implement Infrastructure as Code using AWS CDK or CloudFormation.
• Champion CI/CD automation using GitHub Actions.
• Improve platform observability, monitoring, and operational excellence.

Required Skills & Qualifications

Experience

• 8+ years of experience in Backend, Platform, or Distributed Systems Engineering.
• Proven experience leading technical architecture at Senior, Lead, Staff, or Principal Engineer level.
• Strong experience building enterprise-scale backend platforms.

Technical Skills

• Expert-level programming experience in Python.
• Strong hands-on experience with OpenSearch or Elasticsearch.
• Experience designing distributed, high-performance systems.
• Hands-on experience with Generative AI technologies including:
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Semantic Search
  • Embeddings
  • Vector Search
• Experience with AWS cloud services.
• Knowledge of REST APIs and Microservices architecture.
• Experience implementing CI/CD pipelines using GitHub Actions.
• Strong understanding of Infrastructure as Code (CDK or CloudFormation).

Search & AI Evaluation

• Experience measuring search quality using:
  • Precision
  • Recall
  • NDCG
  • MRR
• Experience building AI evaluation frameworks and benchmarking LLM outputs.
• Understanding of AI regression testing and response quality validation.

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong communication and stakeholder management abilities.
• Proven mentoring and technical leadership experience.
• Ability to influence engineering direction across teams.

Preferred Skills

• Amazon Bedrock
• Amazon SageMaker
• LangChain
• LlamaIndex
• Vector Databases (OpenSearch k-NN, pgvector, Pinecone)
• Search evaluation frameworks
• A/B testing for search relevance
• Online experimentation for AI systems
• CloudFormation
• AWS CDK

Primary Skills

• Python
• OpenSearch
• Elasticsearch
• Generative AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Semantic Search
• Vector Search
• Embeddings
• AWS
• Distributed Systems
• Microservices
• REST APIs
• GitHub Actions
• AWS CDK
• CloudFormation

Good to Have

• Amazon Bedrock
• SageMaker
• LangChain
• LlamaIndex
• Pinecone
• pgvector
• Search Quality Evaluation
• AI Benchmarking
• A/B Testing
• Observability & Monitoring
  
  
  

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