Generative AI / LLM Engineer (2 - 8 yrs)

Generative AI / LLM Engineer (Back-end)

Experience: 2 – 8 Years

Location: Ahmedabad, Gujarat, India

Mode of Engagement: Full-time

Open Positions: 2 – 4

Educational Qualification: B.E / B.Tech / M.Tech / MCA / Computer Science or related field

Industry Preference: AI / SaaS / Software Product / IT Services / Data Engineering Companies

Notice Period: Immediate Joiners Preferred

What We Are Looking For

• 2 – 8 years of hands-on experience in backend software development and distributed systems.
• Strong expertise in Python for backend application development (Node.js or Java a plus).
• Hands-on experience building and deploying Generative AI and LLM-powered applications in production.
• Experience working with OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs.
• Strong understanding of Prompt Engineering, Prompt Chaining, Function Calling, and Agentic AI workflows.
• Experience implementing Retrieval Augmented Generation (RAG) pipelines and contextual AI systems.
• Hands-on experience with vector databases such as Pinecone, Milvus, FAISS, ChromaDB, or similar platforms.
• Strong experience designing and developing RESTful APIs, GraphQL APIs, and microservices architectures.
• Experience working with SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, DynamoDB, or Redis.
• Strong debugging, performance optimization, and problem-solving skills.
• Ability to own services end-to-end and manage multiple development initiatives simultaneously.
• Candidates should be based in Ahmedabad or open to relocating to Ahmedabad
• Hands-on experience with AWS, Azure, or Google Cloud Platform.
• Experience deploying and managing applications using Docker, Kubernetes, and containerized environments.
• Experience building CI/CD pipelines and implementing DevOps best practices.
• Experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar frameworks.
• Good understanding of AI/ML workflows, model lifecycle management, monitoring, and observability.
• Experience implementing authentication, authorization, API security, rate limiting, and compliance controls.
• Prior experience in AI, SaaS, Software Product, or Data Engineering organizations.

Responsibilities

• Design, develop, and maintain scalable backend services for Generative AI and LLM-powered applications.
• Build and integrate REST APIs, GraphQL APIs, and microservices to support AI-driven platforms.
• Implement and optimize Retrieval Augmented Generation (RAG) pipelines and vector search architectures.
• Integrate OpenAI, Azure OpenAI, Anthropic, Gemini, and open-source LLMs into production applications.
• Design and manage prompt orchestration, context management, and AI workflow automation.
• Develop scalable data processing and retrieval systems for AI applications.
• Optimize AI application performance, latency, reliability, and infrastructure costs.
• Build and maintain integrations with vector databases, SQL databases, and NoSQL systems.
• Deploy, monitor, and scale applications using cloud-native technologies and containerized environments.
• Implement security, compliance, authentication, authorization, and API governance best practices.
• Collaborate closely with Data Scientists, ML Engineers, Product Teams, and Frontend Developers.
• Participate in architecture discussions, code reviews, technical documentation, and engineering best practices.
• Monitor AI workloads and implement observability frameworks including logging, metrics, and alerting.
• Continuously evaluate emerging Gen AI technologies and recommend improvements to existing systems.

Qualifications

• Bachelor's or Master's Degree in Computer Science, Information Technology, Engineering, or related field.
• Strong foundation in software engineering principles, backend architecture, and distributed systems.
• Experience working with cloud-native architectures and modern DevOps practices.
• Familiarity with AI/ML concepts, model deployment workflows, and LLM ecosystems.
• Exposure to MLOps, model monitoring, and AI governance practices is preferred.
• Prior experience working in product engineering teams or AI-focused organizations is preferred.