Application Architect

1 week ago

delhi, India Accordion India Full time
Company Overview
Accordion works at the intersection of sponsors and management teams throughout every stage of the investment lifecycle, providing hands-on, execution-focused support to enhance the capabilities of the CFO's office.
So, what does it mean to work at Accordion? It means joining 1,000+ analytics, finance & technology experts in a high-growth, agile, and entrepreneurial environment while changing the way portfolio companies drive value. It also means making your mark on Accordion’s future—by embracing a culture rooted in collaboration and a firm-wide commitment to building something great, together.
Accordion is headquartered in New York City with 10 offices around the globe. Join us
Data & Analytics
Accordion's Data & Analytics (D&A) team offers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges.
We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics.
We deliver data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more.
Location: Hyderabad, Telangana
Role Overview:
Accordion is looking for an experienced Senior Director to lead the Generative AI initiatives drive the strategy, design, and implementation of cutting-edge architectures . (S)he would be collaborating with clients and internal teams to design and recommend scalable and resilient Gen AI architectures, and work with engineering teams to ensure seamless integration and deployment in cloud-based environments. The Senior Director will be a Gen AI evangelist, driving research and development efforts to enhance the team’s expertise in Generative AI and lead knowledge dissemination activities across the organization, serving as an advocate for best practices in AI architecture and development.
What You will do:
Architect scalable and efficient Gen AI solutions that can handle large volumes of data, adapt to changing business requirements, and ensure systems are flexible, robust, and future proof.
Lead the end-to-end implementation of Gen AI and LLM-based applications, overseeing the entire development process from concept to deployment, ensuring alignment with business goals and timely delivery.
Develop prototypes and proof of concepts (PoCs) to validate Gen AI solutions, iterating on models to gather feedback and refine the solution before full-scale implementation.
Ensure seamless integration of Gen AI models with existing enterprise systems and data sources, working closely with technical teams to facilitate efficient data flow and compatibility with enterprise applications.
Implement and maintain CI/CD pipelines, emphasizing automation and scalability to streamline development, testing, and deployment processes for faster iterations and reliable implementations.
Collaborate with cross-functional teams, including data scientists, DevOps, and business stakeholders, to align Gen AI development with strategic goals and address both technical and business challenges effectively.
Provide technical oversight throughout the project lifecycle, ensuring high performance, reliability, and successful delivery through proactive monitoring and troubleshooting.
Establish best practices for application development that focus on maintainability, scalability, and security, ensuring that Gen AI solutions are secure, easy to maintain, and capable of growing with business demands.
Research and track the latest developments in the field to maintain expertise about the latest best practices and techniques within the industry.
Develop accelerators and best practices across various technology stacks to drive efficiency and consistency in project delivery.
Ensure excellence in delivery across projects, maintaining high standards and meeting client expectations.
Lead knowledge management initiatives by developing and maintaining a repository of best practices, case studies, and learning materials.
Conduct webinars, talk shows, and training sessions to share knowledge and expertise, fostering a culture of continuous learning and improvement within the organization.
Ideally, you have:
Undergraduate degree (B.E/B.Tech.) from tier-1/tier-2 colleges are preferred.
10+ years of experience in related field
Deep expertise in AI frameworks and architectures, including large-scale distributed systems and advanced LLM implementations.
Strong experience in developing and implementing Gen AI based applications, , demonstrating expertise in addressing real-world business use cases
Hands-on experience with state-of-the-art LLMs such as OpenAI, Anthropic Claude, Google PaLM 2, and Meta LLaMA2, applying these models to build advanced Gen AI solutions across various domains.
Proficient in software architecture principles, including microservices, API management, and data integration, with experience designing microservices-based systems and integrating Gen AI models into enterprise applications.
Expertise in containerization technologies (e.g., Docker) and orchestration platforms (e.g., Kubernetes), ensuring scalable and reliable system operations for Gen AI solutions.
Strong knowledge of CI/CD pipelines and experience in automating testing, building, and deployment processes to optimize development workflows for Gen AI applications.
Familiarity with caching strategies, containerized environments, and orchestration tools, applying these techniques to improve Gen AI system performance and reduce latency.
Proficiency in AI/ML frameworks and tools such as Lang Chain and Llama Index, enabling efficient development, indexing, retrieval, and chaining of models in Gen AI applications.
Experience with ML Ops and LLM Ops best practices, ensuring smooth deployment, monitoring, and maintenance of large language models in production environments.
Experience with data integration and managing large volumes of data in cloud environments like Azure, AWS, and GCP, ensuring Gen AI systems can effectively leverage diverse data sources.
Familiarity with hyperscale cloud platforms and their AI/ML offerings, leveraging these services to build scalable, high-performance Gen AI solutions.

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