Senior GenAI Engineer - URGENT HIRING - 5+ years of experience

About Senzcraft :

Founded by IIM Bangalore and IEST Shibpur Alumni, Senzcraft is a hyper-automation company. Senzcraft vision is to Radically Simplify Today's Work. And Design Business Process For The Future. Using intelligent process automation technologies.

We have a suite of SaaS products and services, partnering with automation product companies.

Please visit our website - https : / / www.senzcraft.com for more details

Our AI Operations SaaS platform – https : / / MagicOps.ai

Senzcraft on linkedin ->

https : / / www.linkedin.com / company / senzcraft

Senzcraft is awarded by Analytics India Magazine in it’s report “State of AI in India” as a “Niche AI startup”. Senzcraft is also recognized by NY based SSON as a top hyper-automation solutions provider.

About the Role (Senior GenAI Engineer)

Role Overview :

We are seeking a highly skilled Senior GenAI Engineer with 5+ years of experience in AI / ML and automation engineering to design, develop, and deploy production-ready Generative AI solutions. This role requires strong hands-on expertise in LLMs, orchestration frameworks, RAG, embeddings, and MCP integration. You will work across both infrastructure and solution design, translating business needs into robust, scalable GenAI applications.

Key Responsibilities :

• Design & Development : Build and deploy GenAI / LLM-powered applications, integrating frameworks such as CrewAI, LangChain, AutoGen, Semantic Kernel, or LlamaIndex.
• Orchestration & Integration : Develop and maintain Model Context Protocol (MCP) interfaces and servers to enable interoperability across AI / simulation components.
• RAG & Embeddings : Implement efficient Retrieval-Augmented Generation (RAG) pipelines, vector DB integration (Pinecone, FAISS, Chroma), and embedding strategies.
• Prompting & Fine-tuning : Apply prompt engineering, model fine-tuning, and optimization techniques to improve GenAI solutions.
• Application Development : Collaborate with business and application teams to design, prototype, and deploy AI-driven workflows and user-facing features.
• Production-Readiness : Architect, build, and scale agent-based systems for enterprise use cases, ensuring performance, security, and maintainability.
• Cloud & Deployment : Deploy AI / ML workloads on AWS, Azure, and GCP, leveraging services like DynamoDB, storage, compute, and container runtimes.
• Leadership & Collaboration : Lead a team of engineers, providing technical guidance and ensuring alignment with business objectives while also contributing actively to coding and solution development.
• Stakeholder Communication : Engage with both technical and non-technical stakeholders to align AI solutions with business goals.
• Continuous Learning : Stay current with the latest in Generative AI, LLM research, orchestration frameworks, and MLOps / LLMOps practices.

Qualifications :

What Success Looks Like :