Senior Development Lead – AI, RAG Platform

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Software Mind

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

🤖 Artificial Intelligence

☁️ SaaS

📡 Telecommunications

💰 Private Equity Round on 2020-12

Artificial Intelligence • SaaS • Telecommunications

Software Mind is a technology company that specializes in software development and digital transformation services. With a focus on AI and cloud solutions, the company offers a wide range of services including custom software development, mobile app development, and cloud consulting. Software Mind serves various industries such as financial services, telecom, biotech, and media, providing tailored solutions to accelerate digital transformations and business growth globally.

📋 Description

• Lead hands-on development of the AI Extraction Gateway, progressing from Simple RAG to Complex RAG • Implement and tune the expert-weighted (SME) retrieval layer and structured result validation • Own confidence score calibration; collaborate with the BA on accuracy rubrics and test evidence • Drive technical delivery cadence: sprint planning, code reviews, technical risk identification, and team unblocking • Ensure architectural patterns are implemented consistently across the codebase • Collaborate with the Data Engineer on ingestion pipeline integration points and vector store schema • Implement and evolve the query orchestration layer (Python/FastAPI, AWS Lambda/ECS) • Support the QA Automation Engineer in designing the validation harness for RAG outputs • Maintain development observability: structured logging, CloudWatch dashboards, X-Ray tracing

🎯 Requirements

• 6+ years in software development; minimum 2 years in a tech lead or senior engineering lead capacity • Strong Python development skills; FastAPI or equivalent async Python framework required • Hands-on AWS experience: ECS and/or Lambda, API Gateway, DynamoDB, S3, CloudWatch, X-Ray • Experience with vector databases OpenSearch, Pinecone, Weaviate, or equivalent • Solid understanding of API design, service decomposition, and clean backend architecture • AI Experience (Required Not Optional) • Delivered at least one production RAG, semantic search, or LLM-integrated application end-to-end not a prototype or internal tool • Practical experience integrating with LLM provider APIs (OpenAI, Anthropic, or Amazon Bedrock) in a production or enterprise configuration • Working knowledge of chunking strategies, embedding models, retrieval ranking, and prompt engineering in a production context • Experience with confidence scoring, retrieval evaluation, or hallucination mitigation approaches in a deployed system

🏖️ Benefits

• remote work options