Overview

Job Title: AI Engineer – Applied AI Platforms & Solutions

Responsibilities

• Design, develop, and maintain production-ready AI applications and services.
• Build AI-powered document, email, and form ingestion pipelines.
• Develop Retrieval-Augmented Generation (RAG) systems and enterprise knowledge retrieval platforms.
• Design and implement Agentic AI workflows using LangGraph or similar frameworks.
• Integrate LLM APIs including OpenAI, Azure OpenAI, Gemini, Claude, and other AI platforms.
• Develop scalable backend services and APIs using Python and FastAPI.
• Implement document processing, data extraction, embeddings, semantic search, and knowledge retrieval solutions.
• Work with vector databases to support efficient similarity search and retrieval.
• Design reusable AI platform components that can be integrated into enterprise applications.
• Develop REST APIs and microservices for AI-powered applications.
• Deploy and support AI applications on cloud platforms such as Azure, AWS, or GCP.
• Collaborate with developers, architects, and business teams to understand requirements and deliver AI solutions.
• Optimize AI applications for scalability, reliability, performance, and maintainability.

Qualifications

• Location: Ahmedabad / Pune
• Job Type: Full-time
• Work Mode: Work from Office
• Job Summary
• Sigma Solve Ltd. is looking for an experienced AI Engineer – Applied AI Platforms & Solutions to join our team. The ideal candidate will have hands-on experience building and deploying production-ready AI applications using Python, LLMs, RAG, agentic AI frameworks, vector databases, and cloud platforms.
• You will be responsible for developing scalable AI solutions, enterprise knowledge retrieval systems, intelligent automation workflows, and reusable AI platform components.
• 3–6 years of professional software development experience with relevant AI/ML experience.
• Strong programming skills in Python.
• Hands-on experience with FastAPI, Flask, or Django.
• Strong understanding of Generative AI and LLM integration.
• Practical experience with RAG, embeddings, semantic search, and prompt engineering.
• Pinecone
• Qdrant
• ChromaDB
• FAISS
• Azure AI Search
• Similar vector search technologies
• Strong understanding of REST APIs and microservices architecture.
• Understanding of AI application development and deployment practices.
• Good problem-solving and analytical skills.
• Good communication and collaboration skills.
• Knowledge of AI application observability, evaluation, and optimization.
• Familiarity with CI/CD and cloud deployment practices.
• Knowledge of AI security, access control, and responsible AI practices.
• Work Mode: Work from Office
• Work Location: In person

Benefits

• Opportunity to work on real-world enterprise AI projects.
• Exposure to modern Generative AI, RAG, and Agentic AI technologies.
• Opportunity to work with multiple LLM providers and cloud platforms.
• Collaborative and technology-focused work environment.
• Opportunity for professional growth and learning.