Gen ai / llm backend developer ( 3–8 yrs )

Gen AI / LLM Backend Developer
Experience : 5 – 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 / Saa S / Software Product / IT Services / Data Engineering Companies
Notice Period : Immediate Joiners Preferred
What We Are Looking For
5 – 8 years of hands-on experience in backend software development and distributed systems.
Strong expertise in Python, Node.js, or Java for backend application development.
Hands-on experience building and deploying Generative AI and LLM-powered applications.
Experience working with Open AI, Azure Open AI, 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, Chroma DB, or similar platforms.
Strong experience designing and developing RESTful APIs, Graph QL APIs, and microservices architectures.
Experience working with SQL and No SQL databases such as Postgre SQL, My SQL, Mongo DB, Dynamo DB, or Redis.
Hands-on experience with AWS, Azure, or Google Cloud Platform.
Strong experience deploying and managing applications using Docker, Kubernetes, and containerized environments.
Experience building CI/CD pipelines and implementing Dev Ops best practices.
Good understanding of AI/ML workflows, model lifecycle management, monitoring, and observability.
Experience implementing authentication, authorization, API security, rate limiting, and compliance controls.
Strong debugging, performance optimization, and problem-solving skills.
Ability to work independently and manage multiple development initiatives simultaneously.
Candidates should be based in Ahmedabad or willing to relocate to Ahmedabad, Gujarat.
Prior experience in AI, Saa S, Software Product, or Data Engineering organizations is highly preferred.
Responsibilities
Design, develop, and maintain scalable backend services for Generative AI and LLM-powered applications.
Build and integrate REST APIs, Graph QL APIs, and microservices to support AI-driven platforms.
Implement and optimize Retrieval Augmented Generation (RAG) pipelines and vector search architectures.
Integrate Open AI, Azure Open AI, 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 No SQL 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 Dev Ops practices.
Familiarity with AI/ML concepts, model deployment workflows, and LLM ecosystems.
Experience with Lang Chain, Llama Index, Semantic Kernel, Crew AI, Auto Gen, or similar frameworks will be an added advantage.
Exposure to MLOps, model monitoring, and AI governance practices is preferred.
Prior experience working in product engineering teams or AI-focused organizations is preferred.