Headline

Engineering & AI Leader @ Deloitte | Driving AI Transformation & Enterprise Scale Innovation | AI Strategist, Agentic RAG, Responsible AI, DevSecOps, Advanced ML - AI Solutions Architect

About

As an Engineering Manager at Deloitte, I focus on leading enterprise financial analytics transformation by integrating automation, advanced analytics, and AI-driven insights. With deep expertise in critical thinking, AI for business, and productivity enhancement, I define and implement AI/ML and intelligent automation strategies, aligning them with business and technology priorities to deliver measurable outcomes. Enterprise Financial services & AI, Product Engineering, focused on driving digital transformation at scale. Strategic AI & Data Leader with experience in leading teams, architecting and managing Enterprise Data applications, Data Lakes, and AI/ML solutions. Deep expertise in building organizational capabilities, providing thought leadership in the AI and Big Data space. My goal is to bridge the gap between complex AI innovation and sustainable business value.

Location

Hyderabad

AI stack

claude code

github copilot

hugging face

langchain

langfuse

langgraph

Work experience

Engineering Leader at Deloitte, Nov 2025 - Present · 9 mo, Hyderabad, Lead architecture and solution design for enterprise-scale Agentic AI, GenAI, and analytics transformation programs across financial services and global enterprises. Define end-to-end solution architectures encompassing business processes, data platforms, AI services, integration layers, security controls, and cloud infrastructure. Collaborate with business stakeholders, product owners, finance leaders, and technology teams to translate strategic objectives into scalable technology roadmaps. Architect multi-agent AI ecosystems leveraging Azure OpenAI, GPT-4, Llama, and enterprise orchestration frameworks to automate financial reporting, investigations, and decision-support processes. Design enterprise integration patterns connecting ERP, data lakes, warehouses, APIs, and AI platforms to enable real-time insights and workflow automation. Establish architecture governance, responsible AI frameworks, security controls, compliance standards, and operational guardrails for enterprise AI adoption. Lead solution reviews, architecture boards, technology assessments, and executive presentations for senior leadership and client stakeholders. Drive cloud modernization initiatives utilizing Azure, AWS, Kubernetes, Terraform, and DevOps practices to improve scalability, resilience, and cost efficiency. Mentor architects, engineers, and consultants on architecture best practices, AI solution patterns, and enterprise integration strategies. Support business development activities including solution proposals, RFP responses, effort estimation, and client solution workshops.

Senior Technical Manager at R Systems, Sep 2023 - Oct 2025 · 2 yrs 2 mos, Led architecture and delivery of enterprise AI, ML, and GenAI platforms for clients across healthcare, financial services, and SaaS domains. Designed scalable cloud-native solutions for Retrieval-Augmented Generation (RAG), knowledge management systems, intelligent search, and conversational AI platforms. Defined reference architectures, technology standards, and deployment strategies for Azure, AWS, Kubernetes, and distributed data platforms. Collaborated with business and technical stakeholders to gather requirements, conduct solution assessments, and define future-state architecture roadmaps. Architected data ingestion, transformation, storage, and retrieval frameworks supporting large-scale AI and analytics workloads. Designed enterprise RAG frameworks integrating vector databases, embedding models, reranking engines, and domain-specific language models. Established MLOps and LLMOps architectures enabling model lifecycle management, CI/CD automation, monitoring, governance, and operational excellence. Conducted architecture reviews, technology evaluations, and proof-of-concepts to recommend optimal platforms, frameworks, and cloud services. Led cross-functional teams including data engineers, ML engineers, architects, DevOps engineers, and product stakeholders to deliver business-critical solutions. Provided technical leadership during client engagements, solution workshops, architecture reviews, and executive stakeholder discussions.

Technical Project Leader at R Systems, Mar 2022 - Sep 2023 · 1 yr 7 mos, • Led end-to-end development lifecycle of data science projects, achieving a 30% increase in operational efficiency by integrating machine learning models using Python, Docker, Kubernetes, and Kubeflow. • Developed and trained a Generative AI model for defect analysis, achieving an 85% improvement in defect prediction accuracy by leveraging LLMs and fine-tuning techniques. • Deployed and managed machine-learning models on AWS and Azure, ensuring scalability and reliability, while implementing CI/CD pipelines with Jenkins, reducing go-to-market time by 25%. • Developed and trained a large language model using PyTorch, achieving a 30% improvement in natural language understanding, and deployed it using Docker and Kubernetes for scalable and efficient performance. • Developed an AI Python chatbot using open-source Hugging Face models for R Systems. • Conducted code reviews and maintained cloud infrastructure remotely. • Collaborated with the team to refine code and optimize performance. • Achieved seamless integration of open-source models for enhanced user experience.

Lead Data Analyst at American Express, Jan 2019 - Jan 2022 · 3 yrs 1 mo, Gurugram, Haryana, India, - Implement model validation, explainability, and fairness assessments. - Ensure compliance with regulatory requirements and enterprise risk management frameworks. - Establish governance processes for model documentation, approval, and lifecycle management. - Define standards for ethical AI use and risk mitigation. - Translate complex analytical findings into actionable insights for business leaders. - Develop executive dashboards and visualizations to communicate model outputs and trends. - Partner with cross-functional stakeholders to define success metrics and adoption strategies. - Present insights and recommendations to senior leadership. - Design and run experiments to validate model assumptions and measure impact. - Evaluate emerging AI/ML techniques and tools to enhance capabilities. - Drive continuous improvement through experimentation and performance tuning. - Promote a culture of data-driven decision-making.

Data Analyst at American Express, Jan 2016 - Jan 2019 · 3 yrs 1 mo, Gurugram, Haryana, India, • Developed and implemented a credit card processing system using Machine-Learning algorithms, resulting in a 30% reduction in chargeback scenarios and significant cost savings. • Implemented containerization and orchestration technologies, such as Docker and Jenkins CI/CD pipeline, reducing go-to-market time for new features by 25%. • Led the development of a Generative AI model for defect analysis, achieving an 85% improvement in defect prediction accuracy by leveraging LLMs and fine-tuning techniques.

IT Specialist at FIS, Jan 2013 - Jan 2016 · 3 yrs 1 mo, Gurugram, Haryana, India, • Delivered scalable and efficient solutions to complex IT problems, improving system performance and user satisfaction by 30% through advanced machine learning techniques. • Provided technical mentorship, fostering effective task completion and promoting a cohesive work environment, enhancing team productivity by 25%. • Transitioned from manual to automation testing, increasing testing efficiency and accuracy by 70% through active engagement in all phases of the machine learning workflow.

Education

Master of Computer Applications - MCA, Artificial Intelligence, Jain (Deemed-to-be University)

Bachelor's degree, Business Administration and Management, General, manavbhartiuniversity

Public links

github: https://github.com/bhatijagdish