Senior AI Engineer

Key Responsibilities - Design, build, and fine-tune machine learning, deep learning, and Generative AI models for real-world business applications. - Develop Agentic AI systems using frameworks such as ADK, LangGraph, or equivalent for orchestration and reasoning. - Build solutions leveraging LLMs, RAG pipelines, embeddings, and vector databases for enhanced AI capabilities. - Implement AI systems for processing text, structured/unstructured data, and conversational interfaces. - Apply core NLP techniques including classification, summarization, entity recognition, and semantic search to enhance data understanding. - Develop scalable algorithms for search, retrieval, and real-time inference to optimize AI performance. - Integrate AI microservices into enterprise systems using APIs, event-driven architectures, and cloud services like Azure ML, AWS SageMaker, and GCP Vertex AI. Overview - The AI Engineer Manager plays a crucial role in leading and managing a team of AI engineers within the consulting sector. - This position is based in Bangalore, Gurgaon, and Hyderabad, offering a hybrid work model of three days in the office. - The role is aimed at developing innovative AI models and solutions, with a strong focus on Generative AI applications. - As a Level 4 position, it requires 6-9 years of experience, making it ideal for professionals seeking to leverage their expertise in AI to solve complex business problems. - The manager will be responsible for overseeing the design, development, and deployment of AI solutions that directly impact the company's consulting services. - This role involves not only technical proficiency but also leadership skills to guide a team in applying core NLP techniques, building scalable algorithms, and integrating AI microservices into enterprise systems. - The ideal candidate will have a strong understanding of AI concepts, be proficient in Python and SQL, and have hands-on experience with AI frameworks. - They will also be tasked with ensuring that all AI solutions are optimized for performance, cost, and security, while adhering to Responsible AI practices. - The AI Engineer Manager will work closely with solution architects and business teams to translate complex requirements into production-ready AI solutions. - They will champion the development of scalable AI systems that handle text, structured and unstructured data, and conversational use cases. - With responsibilities that include model training, prompt optimization, and data management, this role is pivotal in driving AI innovation and operational efficiency within the organization. - The position offers an opportunity to be at the forefront of AI technology, leveraging cutting-edge tools and frameworks to solve real-world business challenges. - Candidates will be expected to have a solid foundation in Generative AI, cloud platforms, and the deployment of AI workloads. - This role is perfect for those who are passionate about AI and eager to lead a team in a dynamic and fast-paced consulting environment. Requirements - Proficiency in Python, SQL, and machine learning frameworks such as TensorFlow and PyTorch. - Strong understanding of Generative AI concepts, including transformers, embeddings, and fine-tuning. - Experience with Agentic AI frameworks like ADK, LangGraph, and AutoGen for advanced AI model development. - Familiarity with cloud platforms (AWS, Azure, GCP) for deploying AI solutions. - Knowledge of prompt engineering, vector databases (Pinecone, Weaviate), and retrieval-augmented generation (RAG) techniques. - Hands-on experience with cloud-native AI deployments, ensuring efficient and scalable AI solutions. - Understanding of API-driven design, microservices, and event-driven architectures for seamless AI integration.