Custom Software Engineering Lead

Overview

Lead the technical direction, architecture, design and delivery of enterprise-grade custom software and AI-GenAI applications using Python. Drive scalable, secure and production-ready solutions while mentoring teams and making technical decisions.

What you'll do

• Lead the design and development of AI-powered enterprise applications using Python.
• Build and deploy GenAI applications with natural language interfaces.
• Design and optimize RAG, Text-to-SQL, Semantic Search and Agentic AI solutions.
• Integrate and orchestrate LLMs from OpenAI, Gemini, Anthropic and similar platforms.
• Design and implement scalable data ingestion and processing pipelines.
• Develop and manage embeddings, vector stores and retrieval frameworks.
• Establish monitoring, observability and performance dashboards using Grafana.
• Drive technical design decisions, code reviews, mentoring and best practices.
• Collaborate with stakeholders to deliver scalable and secure AI solutions.
• Lead teams through the design and delivery of custom software solutions.
• Set development standards and ensure code quality, scalability and performance aligned to business objectives.

What you'll need

• Minimum 5 year(s) of experience.
• 5+ years of hands-on Python development experience.
• 2+ years of hands-on AI-GenAI application development experience.
• 15 years full time education.
• Strong hands-on coding experience.
• Python, OOPs, Design Patterns and Unit Testing.
• FastAPI, Flask and Django REST Framework.
• SQL, Data Modeling and Shell Scripting.
• Pandas, NumPy and DataFrames.
• Authentication and Authorization using JWT, OAuth and SSO.
• Performance Tuning and Code Optimization.
• LLM Integration using OpenAI, Gemini, Anthropic or similar platforms.
• GenAI Tooling and Natural Language Interface Development.
• Agentic AI Workflows.
• RAG Development and Optimization.
• Text-to-SQL Solutions.
• LangChain, LangGraph, Sentence Transformers and Hugging Face Transformers.
• Vector Search and Semantic Search.
• Embedding Models such as OpenAI, BERT or similar.
• Vector Databases such as FAISS, Qdrant, Weaviate or similar.
• Create and manage Embeddings and Vector Stores.
• Design and implement efficient Data Ingestion and Processing Pipelines.
• Grafana Monitoring and Observability.
• DevOps and Delivery using Git and CI-CD.
• Enterprise Application Development.
• Solution Architecture and Technical Leadership.
• Capability to lead a small team and drive technical decisions.
• Strong problem-solving and debugging skills.
• Experience building production-ready AI-GenAI solutions.
• Excellent communication and stakeholder management skills.

Nice to have

• AI & Data Solution Architecture.
• Azure OpenAI and AWS Bedrock.
• LlamaIndex and MCP.
• Docker and Kubernetes.
• AWS and Azure Cloud.
• Microservices Architecture.

Details

• Location: Mumbai.