Lead AI Architect

As a Lead AI Architect, you will play a crucial role in designing and developing advanced, scalable, AI/ML solutions for the Intapp products. You will work with cross-functional teams to understand business requirements and translate them into scalable and efficient AI architectures and solutions.

You will drive architectural decisions and establish data engineering and AI/ML service design standards, policies, and best practices. Additionally, you will embed Responsible AI principles into every product, focusing on explainability, data drift detection, bias mitigation, and fairness metrics.

You will utilize hands-on experience with evolving AI frameworks and design patterns to ensure successful deployment of AI models in production environments. You will design end-to-end AI solutions, encompassing data collection, preprocessing, model development, deployment, and monitoring. Additionally, implementing AI governance principles and methodologies within AI pipelines and solutions will be critical.

What you will do:

• Architecting and designing scalable, high-performance, reliable, and cost-effective AI software and services for the Intapp suite of products

• Designing and developing AI architectures, frameworks, and algorithms that can support large-scale and sophisticated AI solutions using Retrieval augmented generation (RAG), Contextual AI, Prompt Engineering etc.

• Working on cross-product integration and developing AI solutions that span multiple products

• Working with the Data and AI team leveraging common architectural artifacts to implement data ingestion solutions to support the delivery of AI/ML capabilities deployed across multiple products

• Translating customer requirements into architectural models that operate at large scale, with high performance and deployed on an efficient cloud infrastructure

• Monitoring and measuring the performance, availability, and reliability of AI solutions, and identifying and resolving any issues or risks

• Evaluating and comparing various AI technologies, frameworks, and platforms, such as cloud-based AI services, ML libraries, natural language processing tools, etc.

• Defining, deploying and advancing processes for: AI/ML Development and MLOPS including API-first principles, microservices, SDLC/MDLC (model development life cycle), CI/CD, quality, monitoring, observability, security, extensibility and maintainability of software and services

• Leading by example to review code, look for design breaches, provide meaningful and relevant feedback to data scientists and engineers, stay up to date with system changes

• Collaborating with other product architects, data scientists, developers, testers, and business stakeholders to ensure the quality and consistency of AI solutions

• Developing and presenting business cases, roadmaps, and architectures for AI initiatives, and communicating the value and impact of AI solutions to senior management and stakeholders

• Partnering with development leads to create and promote best practices and standards for AI development and deployment

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What you will need:

• 4+ years of experience in architecting and building AI and ML enterprise-level products or platforms in a SaaS oriented product development organization. Designing cloud native services preferably in Azure

• Demonstrate strong knowledge of AI concepts, technologies, and best practices, and the ability to apply them to solve business problems

• Strong proficiency in Python, SQL, and familiar with frameworks like TensorFlow or PyTorch

• Understanding of machine learning algorithms such as Linear and Logistic regressions, Decision tree, Naive Bayes, KNN, K-means, Random Forest

• Experience in working with and fine-tuning Large Language Models (LLMs) and building scalable applications using LLMs.

• 5+ years of experience in architecting distributed B-2-B based systems in a complex business architecture using microservices, event-driven architecture, and distributed computing.

• 8+ years of previous software engineering experience with proficiency in:

- One or more modern programming languages like Java, Python or C#

- Database (SQL & NoSQL) and vector database technologies

- Enterprise-level caching, messaging and event streaming solutions (Redis, Kafka, Pub Sub, Spark)

- CI/CD, DevOps, and related tooling, including Azure DevOps, Jenkins, etc.

Nice to have:

• Experience building, optimizing deploying ML workflows/pipelines. Experience working with Docker containers and cloud-based computing environments

• Understanding of NLP algorit