GEN AI Engineer - Dehradun (Uttarakhand)

Job Title: AI Engineer (Generative/ Conversational) Location: Dehradun Experience: 4 6 years Team: AI & Automation About the Role We are building AI-driven automation and recruiting products. Our team works on agentic AI systems, RAG-based applications, and workflow automation, integrated into real production processes. Were looking for hands-on AI Engineers who can design, build, and improve AI solutions that work reliably at scalenot just experiments. What Youll Work On - Build RAG-based AI applications using vector databases and LLMs - Develop agentic workflows (multi-step, tool-using AI agents) - Integrate multiple LLMs (OpenAI, Anthropic, open-source models) based on cost, performance, and use case - Fine-tune or adapt models for recruiting and staffing workflows - Work closely with full-stack engineers, UX, BA, and QA to ship production-ready features - Optimize prompts, embeddings, retrieval quality, latency, and cost - Deploy and monitor AI services in real-world automation pipelines Required Skills - Robust Python skills (required) - Experience with LLMs, RAG, and embeddings - Hands-on with LangChain / similar orchestration frameworks - Familiarity with vector databases (Pinecone, FAISS, Weaviate, Chroma, etc.) - Understanding of prompt engineering and model evaluation - Basic knowledge of REST APIs and system integration Good to Have - Experience with agentic AI / tool-using agents - Fine-tuning or LoRA experience - Exposure to cloud platforms (GCP / AWS / Azure) - Experience working on real production AI systems (not only notebooks) - Background in automation, workflows, or SaaS products What We Value - Ability to translate business problems into AI solutions - Curiosity to experiment, measure, and improve - Pragmatic mindset: cost, reliability, and scalability matter - Clear communication and teamwork Why Join Us - Work on real AI products used daily in a US staffing business - Opportunity to grow into senior/lead AI roles - Hands-on exposure to agentic systems and production RAG - Stable, product-focused environment (not a research lab) Job Title: AI Engineer (Generative/ Conversational) Location: Dehradun Experience: 4 6 years Team: AI & Automation About the Role We are building AI-driven automation and recruiting products. Our team works on agentic AI systems, RAG-based applications, and workflow automation, integrated into real production processes. Were looking for hands-on AI Engineers who can design, build, and improve AI solutions that work reliably at scalenot just experiments. What Youll Work On - Build RAG-based AI applications using vector databases and LLMs - Develop agentic workflows (multi-step, tool-using AI agents) - Integrate multiple LLMs (OpenAI, Anthropic, open-source models) based on cost, performance, and use case - Fine-tune or adapt models for recruiting and staffing workflows - Work closely with full-stack engineers, UX, BA, and QA to ship production-ready features - Optimize prompts, embeddings, retrieval quality, latency, and cost - Deploy and monitor AI services in real-world automation pipelines Required Skills - Robust Python skills (required) - Experience with LLMs, RAG, and embeddings - Hands-on with LangChain / similar orchestration frameworks - Familiarity with vector databases (Pinecone, FAISS, Weaviate, Chroma, etc.) - Understanding of prompt engineering and model evaluation - Basic knowledge of REST APIs and system integration Good to Have - Experience with agentic AI / tool-using agents - Fine-tuning or LoRA experience - Exposure to cloud platforms (GCP / AWS / Azure) - Experience working on real production AI systems (not only notebooks) - Background in automation, workflows, or SaaS products What We Value - Ability to translate business problems into AI solutions - Curiosity to experiment, measure, and improve - Pragmatic mindset: cost, reliability, and scalability matter - Clear communication and teamwork Why Join Us - Work on real AI products used daily in a US staffing business - Opportunity to grow into senior/lead AI roles - Hands-on exposure to agentic systems and production RAG - Stable, product-focused environment (not a research lab)