Principal AI Platform & Knowledge Architect

Covalense Digital; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Covalense Digital is seeking a Principal AI Platform & Knowledge Architect to shape the architecture and technical direction for an enterprise AI platform. You will drive RAG, knowledge-driven systems, and Agentic AI workflows across business use cases, while guiding governance, tooling, and scalable design.

You will lead cross-functional teams, evaluate emerging AI technologies, and build production-ready solutions that align with business objectives.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related discipline.
• 10+ years of software engineering, platform engineering, solution architecture, or related roles.
• Proven experience designing and delivering complex enterprise software platforms and data-intensive applications.
• At least 4 years of experience with modern AI technologies in enterprise environments.
• Strong understanding of the AI lifecycle including data prep, analytics, ML, model operationalization, and Generative AI.

Responsibilities

• Define and drive the architecture and technical roadmap for AI-enabled platform capabilities.
• Own end-to-end architecture for RAG, knowledge-driven systems, and Agentic AI workflows.
• Establish architectural standards, governance, and best practices across AI, data, analytics, and platform domains.
• Guide technology selection and drive platform scaling, cost-performance optimization.
• Remain hands-on with prototyping, evaluation of new technologies, and mentoring teams.
• Collaborate with product leadership, engineering teams, and customers to translate business needs into practical technology solutions.

Skills

Architectural leadership

Hands-on execution

Platform engineering

AI in enterprise

Cross-functional collaboration

Cloud-native architectures

Mentoring engineering teams

Kubernetes

AI SDKs

Knowledge graph platforms

Education

Bachelor’s or Master’s in CS/Engineering or related field

Tools

Kubernetes

AI SDKs

Knowledge graph platforms

Job description

About the Role

We are seeking a Principal AI Platform & Knowledge Architect to lead the evolution of our next-generation enterprise Agentic AI platform. This role will be responsible for defining the architecture, technical direction, and implementation strategy for AI-enabled platform capabilities spanning intelligent automation, knowledge-driven systems, enterprise data platforms, advanced analytics, and AI-powered business applications. The successful candidate will combine strong architectural leadership with hands‑on technical execution, helping the organization evaluate emerging technologies, rapidly build proof‑of‑concepts, and establish scalable foundations for future growth. This position will work closely with product leadership, domain experts, engineering teams, and customers to translate business challenges into practical, production‑ready technology solutions.

Key Responsibilities

Platform & Architecture Leadership

• Define and drive the overall architecture and technical roadmap for AI-enabled platform capabilities.
• Own the end-to-end architecture for Retrieval-Augmented Generation (RAG), knowledge-driven systems, and Agentic AI workflows across enterprise use cases.
• Establish architectural standards, design principles, integration patterns, governance controls, and technology best practices.
• Guide technology selection and adoption decisions across AI, data, analytics, application, and platform domains.
• Drive key technical decisions including platform strategy, tooling, build-versus-buy evaluations, scalability considerations, and cost‑performance optimization.
• Ensure solutions are scalable, secure, maintainable, and aligned with business objectives.

AI, Retrieval & Knowledge Systems

• Lead the design of intelligent, knowledge-driven, and automation-focused solutions.
• Define approaches for enterprise knowledge management, information architecture, retrieval systems, semantic technologies, and AI-powered decision support.
• Guide the design of enterprise retrieval architectures including search, ranking, context construction, grounding, and knowledge enrichment approaches.
• Establish frameworks for AI governance, security, observability, evaluation, and operational excellence.
• Drive innovation through continuous assessment of emerging AI technologies and industry trends.

Hands-On Technical Leadership

• Remain actively involved in technical implementation, prototyping, and proof-of-concept development.
• Evaluate new technologies, frameworks, platforms, and approaches through practical experimentation.
• Lead architecture reviews, mentor engineering teams, and establish engineering and AI best practices.
• Support complex solution design, customer engagements, and strategic initiatives.

Cross-Functional Collaboration

• Work closely with product management, engineering, data teams, and business stakeholders.
• Translate business requirements into technology strategies and implementation plans.
• Support the development of reusable platform capabilities that accelerate future product delivery.
• Drive organization-wide AI adoption and innovation initiatives by identifying opportunities to improve business processes, engineering productivity, customer experience, and operational efficiency through practical application of AI technologies.
• Act as a trusted advisor to leadership on emerging AI opportunities, risks, and technology strategy.

Required Experience & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related discipline.
• 10+ years of experience in software engineering, platform engineering, solution architecture, enterprise architecture, or related roles.
• Demonstrated experience designing and delivering complex enterprise software platforms, distributed systems, and data-intensive applications. Proven hands‑on experience deploying production-grade systems handling complex workflows, integrations, and large‑scale data processing.
• At least 4 years of experience working with modern AI technologies and their practical application within enterprise environments.
• Strong understanding of the broader AI lifecycle including data preparation, analytics, machine learning, model operationalization, knowledge systems, and Generative AI technologies.
• Experience working across multiple technology domains including applications, platforms, data, analytics, integration, and cloud-native environments.
• Proven ability to lead technical decisions and influence architecture across teams.
• Strong hands‑on software engineering background with modern development practices.

Desired Skills & Experience

• Experience building AI-powered applications, intelligent automation solutions, analytics platforms, or decision-support systems.
• Exposure to agent-based systems, workflow orchestration frameworks, retrieval-based AI applications, and large language model ecosystems.
• Experience with modern AI application development frameworks, agent development SDKs, or AI orchestration platforms.
• Strong understanding of enterprise data platforms, data engineering, analytics, semantic layers, and information architecture.
• Experience designing event-driven architectures, asynchronous workflows, integration platforms, and scalable distributed systems.
• Experience with AI governance, security, compliance, monitoring, observability, evaluation, and operationalization.
• Familiarity with cloud-native architectures, containerization, Kubernetes, and modern deployment practices.
• Experience working with knowledge-centric platforms, semantic technologies, enterprise search solutions, or knowledge graph concepts.
• Understanding of platform reliability, observability, monitoring, and operational excellence practices.

Good to Have

• Exposure to AI infrastructure, model serving platforms, inference optimization, or GPU-enabled environments.
• Familiarity with open-source foundation models, model customization, fine-tuning approaches, and AI evaluation methodologies.
• Exposure to AI security frameworks, guardrails, prompt safety, policy enforcement, and responsible AI practices.
• Experience with multi-tenant enterprise platforms and SaaS architectures.

Preferred (Not Mandatory) Industry Experience

• Telecommunications, digital service providers – Exposure to customer management, product management, operations, billing, CRM, or digital transformation initiatives.

What We Are Looking For

We are looking for a technology leader who combines strong systems thinking with a pragmatic, delivery-oriented mindset. The ideal candidate is equally comfortable discussing long-term architecture strategy and building a working prototype. They are naturally curious, stay current with rapidly evolving technologies, and have the ability to assess innovation through practical experimentation rather than theory alone. Experience working in product companies, startups, or fast-moving innovation environments will be highly valued.