
Covasant provides autonomous AI solutions that automate and optimize business processes. It uses an AI-led Services as a Software approach to deliver scalable, agentic capabilities. Core tech includes personalization, custom model development, and deep industry knowledge. The company targets enterprises with B2B implementations and aims to integrate into existing workflows. Overall, Covasant focuses on improving decision quality and operational efficiency at scale.

Covasant provides autonomous AI solutions that automate and optimize business processes. It uses an AI-led Services as a Software approach to deliver scalable, agentic capabilities. Core tech includes personalization, custom model development, and deep industry knowledge. The company targets enterprises with B2B implementations and aims to integrate into existing workflows. Overall, Covasant focuses on improving decision quality and operational efficiency at scale.
About the Role
We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems — ensuring production-grade quality, scalability, and compliance. You will interface with cross-functional teams, manage engineering complexity, and ensure value realization for customers across industries such as BFSI, HLS, Manufacturing, CMT, Retail, and Energy.
Key Responsibilities
Architecture & Technical Leadership
Own the end-to-end technical architecture and solution integrity during project delivery.
Translate solution blueprints into detailed technical designs, backlog, and integration plans.
Lead detailed design reviews, ensure alignment with AI platform, MLOps, and Agentic AI best practices.
Select appropriate frameworks, APIs, libraries, and cloud-native services for implementation.
Serve as technical anchor for customer AI/ML and Agentic AI projects.
Guide engineering teams on modular, secure, and reusable implementation strategies.
Review and validate code, infrastructure scripts, and ML pipelines for quality, performance, and reliability.
Oversee data pipelines, model training, LLMOps, and model deployment workflows.
Provide hands-on support for complex components: LLM pipelines, vector stores, fine-tuning, evaluations.
Resolve system integration challenges across APIs, knowledge stores, and orchestration layers.
Implement or validate MLOps workflows using MLflow, Airflow, Argo, KServe, BentoML, etc.
Please share your profiles on karuna.vempala@covasant.com