Senior GenAI Engineer
Crossing Hurdles
5 - 10 years
Mumbai
Posted: 10/01/2026
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Job Description
Crossing Hurdles is a global recruitment consultancy partnering with an AI-powered technology services company. We are looking for talent with hands-on Large Language Model (LLM) experience to help solve complex business problems for Fortune 500 clients. The work involves building industry-leading multi-agent LLM systems, RAG pipelines, and deploying open-source LLM solutions at scale.
Required skills
- 8+ years of professional experience in building Machine Learning models & systems for Sr GenAI Engineer and 10+ years for Staff GenAI Engineer
- 1+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.
- Expert proficiency in programming skills in Python, Langchain/Langgraph and SQL is a must.
- Understanding of Cloud services from various cloud services from Azure, GCP, or AWS for building the GenAI applications
- Excellent communication skills to effectively collaborate with business SMEs
Roles & Responsibilities
- Develop and optimize LLM-based solutions : Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
- Codebase ownership : Maintain high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
- Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
- Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
- Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
- Continuous innovation : Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.
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