• Define and champion the company's multi-year data and AI strategy, aligning it with overall business objectives and growth plans. • Identify high-impact opportunities for leveraging generative AI, machine learning and advanced analytics across product development, operations, sales, and marketing. • Establish data governance policies, data quality standards, and ethical AI practices to ensure data integrity, security, and compliance. • Recruit, mentor, and lead high-performing teams of Data Engineers, Data Analysts, Data Scientists, AI Infra, AI and ML Engineers. • Foster a data-driven culture across the organization, promoting data literacy and the use of analytical insights in daily decision-making. • Oversee the architecture, development, and maintenance of scalable and reliable data platforms (e.g., data warehouse, data lake, ML and AI Platform infrastructure). • Drive the end-to-end lifecycle of AI/ML projects, from ideation and experimentation to deployment, monitoring, and measurable business impact. • Manage budgets, technology selection, and vendor relationships related to data and AI infrastructure and tooling. • Partner closely with Product, Engineering, Clinical and Operations leaders to embed data and AI capabilities into core products and business processes. • Act as the primary evangelist for data and AI capabilities internally and externally. • Present strategy, roadmaps, and key results to the executive team and board of directors.

Role Description The experienced AI Architect with deep expertise in Generative AI will lead the design, development, and deployment of scalable AI solutions for our clients. This role combines strategic advisory capabilities with hands-on architectural leadership across both traditional machine learning and modern generative AI systems. - Design and architect end-to-end AI/ML and Generative AI solutions aligned with client business objectives. - Lead development of AI systems including LLM-powered applications, predictive models, and intelligent automation. - Architect RAG (Retrieval-Augmented Generation) pipelines and vector database solutions. - Evaluate, select, and integrate foundation models (e.g., OpenAI, open-source LLMs, fine-tuned models). - Define best practices for AI solution design, scalability, performance, and governance. - Establish standards for prompt engineering, model evaluation, and responsible AI guardrails. - Design and oversee data pipelines, ETL processes, and supporting data architecture. - Collaborate with cross-functional teams (data scientists, engineers, business stakeholders) to deliver solutions. - Ensure compliance with security, privacy, and ethical AI principles. - Provide technical leadership, mentorship, and architectural guidance to project teams. - Support pre-sales and client engagements, including solution design and presentations. - Stay current with emerging AI trends, especially in Generative AI and enterprise adoption patterns. Qualifications - Hands-on experience with Generative AI and LLM-based systems. - Strong expertise in: - Machine learning frameworks (TensorFlow, PyTorch, scikit-learn) - Large Language Models (LLMs) and transformer-based architectures - Prompt engineering and RAG design patterns - Experience with GenAI orchestration frameworks (e.g., LangChain, LlamaIndex). - Proficiency in Python (and optionally Java/Scala). - Experience with cloud platforms (AWS, Azure, or Google Cloud) and MLOps/LLMOps practices. - Solid understanding of APIs, microservices, distributed systems, and data pipelines. - Experience fine-tuning or training foundation models. - Familiarity with multimodal AI (text, image, audio, video). - Experience with vector databases (e.g., Pinecone, FAISS, Weaviate). - Background in consulting or client-facing environments. - Knowledge of containerization and orchestration (Docker, Kubernetes). - Understanding of AI governance, regulatory considerations, and model risk management. - Industry experience in sectors such as healthcare, financial services, or retail. - Deep expertise in AI/ML and Generative AI technologies. - Strong system architecture and design capabilities. - Strategic thinking with the ability to align AI solutions to business outcomes. - Excellent communication and stakeholder management skills. - Leadership, mentoring, and cross-functional collaboration. Requirements - Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field. - At least 7 years of experience in software engineering, data engineering, or AI/ML development. - At least 3 years of experience designing and deploying AI/ML architectures at scale. Physical Requirements - Prolonged periods of sitting at a desk and working on a computer. - Must be able to lift up to 15 pounds at times.

• Design, develop and maintain AI/ML solutions for various business units. • Drive end-to-end AI/ML development including data preparation, model development/training, testing and performance monitoring. • Integrate models into workflows to support Operational goals. • Ensure solutions abide by stated organizational policies including data security and privacy. • Monitor model performance and continuously improve accuracy and reliability. • Work closely with operations, client services and IT teams to define automation needs and business requirements. • Translate operational challenges into analytical frameworks and AI solutions. • Present complex insights in clear, actionable language for management, Operations and IT staff. • Support automation initiatives that reduce manual processing and improve efficiency.

About Us “Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. WHY JOIN CAPCO? You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry. MAKE AN IMPACT Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services. #BEYOURSELFATWORK Capco has a tolerant, open culture that values diversity, inclusivity, and creativity. CAREER ADVANCEMENT With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands. DIVERSITY & INCLUSION We believe that diversity of people and perspective gives us a competitive advantage. MAKE AN IMPACT Job Details AI Engineer: Key Responsiblities: 1. System Development: Designing and building AI models, such as neural networks, that learn from data and mimic human cognitive functions 2. Production Deployment: Transitioning research-level ML models into scalable, operational applications via APIs, microservices, or cloud platforms. 3. Data Handling & Training: Selecting, managing, and training models using large datasets, including natural language processing (NLP) and computer vision tasks. 4. Testing & Optimization: Evaluating accuracy, debugging, and improving AI performance to ensure systems run efficiently. 5. Collaboration: Working with data scientists and software engineers to align AI solutions with business objectives. Required Skills and Qualifications: 1. Programming languages: Strong proficiency in Python, Java, or C++. How to use AI tooling to build up capability. Any UI/API automation framework. 2. ML Frameworks: Experience with TensorFlow, PyTorch, Keras, or Scikit-learn. How to use MCP server. 3. Data & Cloud Tools: Proficiency in SQL, Big Data Technologies, and cloud platforms like AWS SageMaker, Azure ML, or Google Cloud 4. Technical Skills: Expertise in machine learning, deep learning, NLP, computer vision, and algorithm development. 5. Education: Typically requires a Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.