Senior AI Engineer

Job Responsibilities - Responsible for designing, building, and maintaining scalable AI solutions - Develop and implement advanced Generative AI solutions (LLMs, embeddings, retrieval techniques, prompt engineering) - Ensure that data architectures and infrastructure can scale seamlessly as the data volume and complexity grow - Lead, mentor, and develop a team of AI Engineers, fostering a collaborative and inclusive team environment - Identify and address skill gaps, and provide opportunities for professional development - Coordinate with stakeholders to gather requirements, set priorities, and define project timelines - Ensure projects align with overall business objectives and data strategy - Ensure data quality, integrity, and security across all data engineering projects - Identify opportunities for process improvements and drive initiatives to enhance the efficiency and effectiveness of data operations - Ability to build/drive reusable frameworks that can drive efficiency of the overall data system - Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes Required Skills (Must have) Tech: - Experience of 4.5-7 years in development and deployment of scalable AI/ML solutions - Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc - Develop and implement advanced Generative AI solutions (LLMs, embeddings, retrieval techniques, prompt engineering) - Design and optimize Retrieval-Augmented Generation (RAG) solutions - Manage Databricks workflows, including job and cluster creation also Databricks API - Apply data structures and algorithms knowledge, including multiprocessing and optimization techniques - Utilize Python libraries (Pandas, Numpy, FastAPI) for data processing and API development - Perform SQL optimization and database architecture design (schema creation, normalization, functions, triggers) - Deploy and orchestrate AI models using Docker and Kubernetes - Collaborate using GitHub for version control and team collaboration - Work with cloud platforms for AI solution deployment and management (Azure, GCP, AWS) - Utilize PySpark for data processing (optional) - Basic understanding of CI/CD pipelines and deployment process Non-Tech: - Strong problem-solving skills with an ability to assess the financial impact of decisions, both in running the delivery team and delivering solutions to clients - Proficient in written and verbal communication and able to hold conversations with mid-management-level clients - Ability to recognize pragmatic alternatives vis-à-vis a perfect solution and get the delivery teams on board to pursue them, balancing time priorities with potential business impact - Strong people skills, including conflict resolution, empathy, communication, listening, and negotiation - Shows proficiency in providing technical guidance and provide leadership and mentorship to the delivery team Good to Have Skills - Familiarity with data visualization tools and techniques - Knowledge of data security and privacy practices - Understanding of data governance and compliance frameworks - Experience with graph databases and graph processing frameworks - Experience with data virtualization and data federation techniques - Proficiency in data profiling and data quality management - Self-driven with a strong sense of ownership