Sr. AI Engineer-Promo Optimisation

Target is hiring a Sr. AI Engineer-Promo Optimisation in Bangalore.

Responsibilities

• Build production-grade AI/ML applications, services, and platforms using Python and modern engineering practices, with a focus on clean code, testing, documentation, reliability, scalability, and maintainability.

• Design and develop scalable data and ML pipelines for batch, streaming, and near-real-time processing using distributed data frameworks, Kafka or event-driven architecture, workflow orchestration tools, and enterprise data platforms.

• Implement end-to-end model training, evaluation, deployment, inference, monitoring, and lifecycle management workflows that can scale across large datasets and high-impact enterprise use cases.

• Partner with Data Scientists to convert prototypes, notebooks, statistical models, ML models, GenAI workflows, and optimization algorithms into reliable, reusable, and production-ready systems.

• Build and deploy REST APIs, microservices, model-serving endpoints, batch scoring jobs, and event-driven integrations that expose AI/ML capabilities to downstream applications and business workflows.

• Design scalable inference systems for promotion decisioning, segmentation, redemption prediction, offer ranking, campaign simulation, and personalized marketing use cases.

• Work with SQL, NoSQL, object stores, feature stores, and distributed data systems to store, retrieve, transform, and manage structured and unstructured data for AI/ML applications.

• Support production deployment and release management through CI/CD, containerization, automated testing, model versioning, automated validation, release controls, rollback strategies, and environment management.

• Implement MLOps capabilities including feature pipelines, model registries, experiment tracking, automated retraining, performance monitoring, data drift detection, model drift detection, lineage, governance, and reproducibility.

• Implement observability and reliability mechanisms, including logging, metrics, traces, dashboards, alerting, error handling, incident response, and root-cause analysis for production AI systems.

• Optimize AI/ML services for latency, throughput, cost, scalability, reliability, and operational performance.

• Evaluate and integrate Generative AI and LLM components, including prompt workflows, RAG pipelines, embeddings, vector databases, model evaluation, guardrails, safety controls, and orchestration patterns where applicable.

• Explore agentic AI workflows, including planning, tool use, multi-step reasoning, workflow orchestration, and human-in-the-loop patterns for internal productivity and decision-support use cases.

• Contribute to design reviews, architecture discussions, code reviews, operational readiness reviews, and engineering standards for AI/ML systems.

• Troubleshoot production issues across data pipelines, model services, APIs, optimization workflows, and downstream integrations; identify root causes and implement durable fixes.

• Create reusable frameworks, libraries, templates, and best practices that improve AI engineering velocity and quality across the team.

About Target

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America’s leading retailers. Joining Target means promoting a culture of mutual care and respect while striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you’ll build relationships by being authentic and respectful.