AI Engineer Role Summary: We are seeking an AI Engineer with a strong background in Generative AI, Natural Language Processing (NLP), Large Language Models (LLMs), and agentic AI to join our growing team. You will focus on building robust, scalable AI solutions that harness Azure AI capabilities, with a strong emphasis on MLOps and LLM frameworks. You should have a passion for crafting high-quality, production-ready AI systems and a proven track record of delivering impactful solutions. Key Responsibilities: * Design & Develop: Architect and implement Generative AI applications using Azure OpenAI Services, Azure Machine Learning, and other Azure AI tools. Develop and fine-tune LLMs for domain-specific tasks using popular frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or similar. Build agentic AI systems capable of autonomous reasoning and task execution. * NLP and Advanced Language Models: Work with Natural Language Processing pipelines, including text classification, summarization, entity extraction, and question answering. * MLOps & Azure Integration: Familiarity with CI/CD pipelines, model versioning, deployment, and monitoring for AI models using Azure Machine Learning MLOps capabilities. Collaborate with DevOps team to ensure seamless integration of models into production systems. * Innovation & Scalability: Stay at the forefront of AI advancements, particularly in LLMs and Generative AI, to continuously enhance our AI solutions. Drive the adoption of best practices for scalable and secure AI system development on Azure. * Mentorship & Collaboration: Provide technical mentorship to junior engineers and contribute to knowledge-sharing within the team. Collaborate closely with cross-functional teams (Product, Engineering) to translate business requirements into technical solutions. Qualifications & Skills: * Experience: Minimum 4 years of experience in AI engineering, with a strong focus on Generative AI, LLMs, and NLP. Proven experience building and deploying AI models using Azure AI capabilities, including Azure OpenAI, Azure ML, and Azure Cognitive Services. Solid experience with LLM frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Hands-on experience with MLOps pipelines and CI/CD practices. * Technical Skills: Proficiency in Python (including libraries like PyTorch, TensorFlow, and popular LLM frameworks). Strong understanding of LLM fine-tuning, prompt engineering, embedding models, and vector databases (e.g., Azure AI Search, Pinecone, Weaviate). Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure, with a preference for Azure. * Soft Skills: Excellent problem-solving skills, with a focus on delivering production-ready solutions. Strong communication and collaboration abilities, with a knack for explaining complex AI concepts to non-technical stakeholders. PS:- This Opportunity is for Gurugram location only.
The Role The implementation consultant will be responsible for leading the end-to-end implementation of HUB for new and existing clients. This includes gathering requirements, understanding data, solution design, configuration, data migration, integration, training, and go-live support . You will work closely with clients to ensure a seamless onboarding experience while collaborating with internal teams across product, engineering, and customer success , with the main goal for delivering value to the customer and supporting their HUB rollout. Accountabilities Engage with client stakeholders (operations, IT, finance) to understand workflows and business objectives. Document functional and technical requirements aligned with best practices. Design solutions leveraging HUB capabilities for NAV oversight, performance management, reporting and post trade. Configure the SaaS platform, ensuring alignment with client requirements. Coordinate internal and client resources to meet implementation goals. Manage data mapping, cleansing, and migration activities. Work with APIs and integration frameworks to connect the platform to market data providers, OMS/EMS, custodians, and other third-party servicer & systems. Conduct end-user training sessions and produce user documentation. Ensure smooth knowledge transfer to client teams. Support user testing and go live process. Provide hypercare and post-go-live support to ensure adoption. Maintain strong client relationships, escalate issues and manage expectations effectively. Deliverables Successful delivery of end-to-end customer go lives Translated stakeholder requirements, including Customer, Design, technology to feed product evolution Contribute to, and drive customer user engagement in delivery process Consistently meet or exceed expectations when evaluated against HUBs core values and technical standards Own your personal continued development About you: Must have Minimum 5+ years’ business analysis or relevant experience Agile experience – working within client implementations Technical experience such as SQL, APIs and integration frameworks Experience working with internal or external customer stakeholders Asset management / financial services experience Proactive, dynamic self-starter who is hands-on and can work across numerous teams in the business A team player, able to work in a collaborative and supportive environment to get things done Someone who can influence decisions, push things along and generally is eager to support moving the product delivery process forward Nice to have. Understanding of integration and functional architecture Knowledge of the Azure cloud stack
Role Summary: We are seeking an AI Engineer with a strong background in Generative AI, Natural Language Processing (NLP), Large Language Models (LLMs), and agentic AI to join our growing team. You will focus on building robust, scalable AI solutions that harness Azure AI capabilities, with a strong emphasis on MLOps and LLM frameworks. You should have a passion for crafting high-quality, production-ready AI systems and a proven track record of delivering impactful solutions. Key Responsibilities: * Design & Develop: Architect and implement Generative AI applications using Azure OpenAI Services, Azure Machine Learning, and other Azure AI tools. Develop and fine-tune LLMs for domain-specific tasks using popular frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or similar. Build agentic AI systems capable of autonomous reasoning and task execution. * NLP and Advanced Language Models: Work with Natural Language Processing pipelines, including text classification, summarization, entity extraction, and question answering. * MLOps & Azure Integration: Familiarity with CI/CD pipelines, model versioning, deployment, and monitoring for AI models using Azure Machine Learning MLOps capabilities. Collaborate with DevOps team to ensure seamless integration of models into production systems. * Innovation & Scalability: Stay at the forefront of AI advancements, particularly in LLMs and Generative AI, to continuously enhance our AI solutions. Drive the adoption of best practices for scalable and secure AI system development on Azure. * Mentorship & Collaboration: Provide technical mentorship to junior engineers and contribute to knowledge-sharing within the team. Collaborate closely with cross-functional teams (Product, Engineering) to translate business requirements into technical solutions. Qualifications & Skills: * Experience: Minimum 4 years of experience in AI engineering, with a strong focus on Generative AI, LLMs, and NLP. Proven experience building and deploying AI models using Azure AI capabilities, including Azure OpenAI, Azure ML, and Azure Cognitive Services. Solid experience with LLM frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Hands-on experience with MLOps pipelines and CI/CD practices. * Technical Skills: Proficiency in Python (including libraries like PyTorch, TensorFlow, and popular LLM frameworks). Strong understanding of LLM fine-tuning, prompt engineering, embedding models, and vector databases (e.g., Azure AI Search, Pinecone, Weaviate). Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure, with a preference for Azure. * Soft Skills: Excellent problem-solving skills, with a focus on delivering production-ready solutions. Strong communication and collaboration abilities, with a knack for explaining complex AI concepts to non-technical stakeholders. Good to have: Experience with backend development, especially in building APIs or integrating AI models into web applications Familiarity with Node.js and related frameworks for developing and deploying scalable backend services. .