Senior Agentic AI & Data Science Engineer

About the job

We are hiring a talented Senior Agentic AI & Data Science Engineer (Product Engineering) to join our team. If you're excited to be part of a winning team, CirrusLabs ( http://www.cirruslabs.io ) is a great place to grow your career. Experience - 7-10 years Location - Bengaluru Work Timings - 2pm - 11pm IST Experience 7–10 years total experience in Data Science, AI/ML Engineering, and Product Engineering Strong hands-on experience in building, deploying, and scaling Agentic AI systems in production Role Summary We are looking for a Senior Agentic AI & Data Science Engineer with a deep product engineering background to architect, develop, deploy, and operate production-grade AI systems. The role requires end-to-end ownership of AI products—covering agent design, ML modeling, system architecture, MLOps, multi-cloud deployment, security, and scalability. The ideal candidate combines strong AI research intuition with real-world engineering excellence. Core Responsibilities Agentic AI & LLM Systems • Design, implement, and optimize Agentic AI architectures involving planning, reasoning, memory, tool-use, and orchestration. • Build and manage multi-agent systems for complex workflows, automation, and decision intelligence. • Implement Retrieval-Augmented Generation (RAG) pipelines with structured and unstructured data sources. • Integrate AI agents with enterprise APIs, databases, SaaS platforms, and internal tools. • Develop robust prompt strategies, agent workflows, fallback mechanisms, and evaluation pipelines. • Deploy and operate LLM-based systems with cost, latency, reliability, and safety considerations. Data Science & Machine Learning • Build, train, evaluate, and deploy ML/DL models across NLP, structured data, time-series, recommendation, and predictive analytics. • Perform data exploration, feature engineering, statistical analysis, and hypothesis testing. • Design scalable training pipelines, experiment tracking, and model versioning. • Monitor model performance, drift, bias, and data quality in production environments. • Apply explainability and interpretability techniques where required. Product Engineering & System Design • Own the full AI product lifecycle : problem definition → design → development → deployment → monitoring → iteration. • Translate business and product requirements into scalable, modular, and maintainable AI solutions. • Design distributed, fault-tolerant, and extensible architectures for AI platforms. • Collaborate closely with product managers, UX, backend, frontend, and platform teams. • Enforce engineering best practices including code quality, testing, documentation, and performance optimization. Multi-Cloud & Infrastructure Engineering • Design, deploy, and operate AI systems across AWS, Azure, and GCP (multi-cloud or hybrid). • Use Docker, Kubernetes, Helm, and cloud-native services for scalable deployments. • Implement Infrastructure as Code (IaC) using Terraform / CloudFormation. • Leverage managed AI/ML services where appropriate (SageMaker, Vertex AI, Azure ML). • Optimize cloud resource utilization and cost across environments. Security, Governance & Reliability • Ensure data security, privacy, and compliance across AI systems. • Implement secure access control, secrets management, and encrypted data pipelines. • Apply Responsible AI practices : bias detection, fairness, explainability, auditability. • Design systems for high availability, disaster recovery, and fault tolerance. • Establish governance standards for models, data, and AI agents. Technical Leadership & Collaboration • Provide technical guidance and mentorship to junior engineers and data scientists. • Lead architecture discussions, technical reviews, and best-practice adoption. • Drive innovation in AI/Agentic systems aligned with product and business goals. • Communicate complex technical concepts clearly to both technical and non-technical stakeholders. Cloud, DevOps & MLOps • Strong hands-on experience with AWS, Azure, and/or GCP (at least two preferred) • Docker, Kubernetes, Helm • CI/CD: GitHub Actions, GitLab CI, Jenkins • MLOps tools: MLflow, Kubeflow, cloud-native ML platforms • Monitoring and observability tools Architecture & Distributed Systems • Distributed systems and event-driven architectures • Asynchronous processing and workflow orchestration • Scalability, reliability, and performance engineering

Requirements

• AI Engineering
• MLOps
• Data Science
• ML Models
• Cloud Computing

Qualifications

• 7-10 years experience
• Strong hands-on experience in Agentic AI systems

Preferred Technologies

• AI Engineering
• MLOps
• Data Science
• ML Models
• Cloud Computing

About the company

We are CirrusLabs. Our vision is to become the world's most sought-after niche digital transformation company that helps customers realize value through innovation. Our mission is to co-create success with our customers, partners and community. Our goal is to enable employees to dream, grow and make things happen. We are committed to excellence. We are a dependable partner organization that delivers on commitments.