Tech Lead - Software Engineer
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Role details
Tech stack
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Job description
Golang (Go) , Agentic AI , Generative AI , and AI architecture . The role involves designing scalable backend services, building AI powered applications, integrating LLMs, implementing RAG and agentic workflows, and developing cloud native AI platforms. Key Responsibilities Design and develop scalable, high performance APIs and backend services using Golang (Go) . Build Agentic AI and Generative AI applications using LLMs such as OpenAI, Gemini, Claude, and open source models. Design AI architectures for LLM powered applications, autonomous agents, tool calling, and multi agent workflows . Develop and maintain REST and gRPC APIs and microservices for AI platforms. Design and implement RAG architectures , including document ingestion, chunking, embeddings, retrieval, reranking, and LLM response generation. Work with vector databases such as Weaviate for semantic search and knowledge retrieval. Develop full stack AI applications using Golang, JavaScript, and modern web technologies . Integrate AI services with PostgreSQL, MongoDB, and vector databases . Containerize and deploy applications using Docker and support cloud native environments such as OpenStack . Design secure and reliable communication between distributed microservices and AI components. Troubleshoot performance, scalability, API, infrastructure, and networking related issues . Implement observability, error handling, authentication, authorization, and production grade API practices. Collaborate with AI architects, product teams, DevOps, and engineering teams to deliver end to end AI solutions.
Requirements
Software Engineering, Technical Leadership, Artificial Intelligence (AI), Go Programming Language (Golang), Cloud Computing, Application Programming Interface (API), REST (Representational State Transfer), Microservices, Identify Issues, Error Handling, Strong hands on programming experience with Golang (Go) . Strong knowledge of Agentic AI, Generative AI, LLMs, prompt engineering, and AI application architecture . Experience building applications using OpenAI, Gemini, Claude, or open source LLMs . Hands on experience with RAG, embeddings, vector search, and vector databases , preferably Weaviate. Strong experience with REST APIs, gRPC, microservices, concurrency, and distributed systems . Experience with PostgreSQL and MongoDB . Full stack development exposure with JavaScript . Experience with Docker and OpenStack . Solid networking knowledge including TCP/IP, DNS, HTTP/HTTPS, load balancing, proxies, API gateways, TLS, and service to service communication . Understanding of AI application security, scalability, performance optimization, and production deployment.
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