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Target

Sr AI Engineer

Target

Location
Onsite (Bengaluru, Karnataka)
Employment
Full-time
Level
Mid Level
Posted 1 week ago

About the Role

Target's Advanced AI team in Bengaluru builds production-grade AI/ML applications to drive business automation and insights. The Senior AI Engineer role focuses on developing scalable, reliable systems using LLMs and agentic architectures to solve complex business problems.

Skills

Python Machine Learning Deep Learning PyTorch TensorFlow LangChain LlamaIndex Semantic Kernel LLMs Agentic Systems Software Engineering API Development Cloud Platforms CI/CD Data Pipelines System Design

Full job details

About Us

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 and 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.

Overview about TII

At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.

Pyramid Overview

A role with Target Data Science & Engineering means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Statistics, Optimization or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Network Security and Personalization rely on.

Team Overview

Target’s Advanced AI team builds end-to-end AI/ML systems that create meaningful business value across the enterprise. These systems may be powered by LLMs, classical machine learning, or deep learning models, and are designed as scalable, reliable, production-grade applications, including agentic architectures where they add clear value.

Role Overview

As a Senior AI Engineer for Advanced AI, you will help build, deploy, and maintain AI/ML applications that support automation, insight, and action across core business workflows. You will work closely with Data Scientists, engineers, product partners, platform teams, security teams, and business stakeholders to turn well-defined and moderately ambiguous business problems into practical technical solutions.

In this role, you will contribute hands-on to the development of production-grade AI applications. You will write maintainable, well-tested code, support model and framework integration, build APIs and services, develop data and application workflows, and contribute to deployment, monitoring, documentation, and production support. You will help ensure AI applications are secure, reliable, maintainable, and aligned to Target’s enterprise standards for infrastructure, platform architecture, data handling, and operational readiness.

You will also partner with Lead and Principal Engineers to evaluate technical options, identify implementation risks, resolve engineering roadblocks, and improve reusable AI engineering patterns. This role requires curiosity and continuous learning, including staying current with developments in AI, machine learning, LLMs, agentic systems, and modern software engineering practices. A successful Senior AI Engineer will help deliver high-quality AI applications that create measurable business value while contributing to the technical strength of the team.

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs. 

About you:

  • 4-year degree or equivalent experience.

  • 3+ years of hands-on software engineering experience, including experience building or supporting production systems.

  • Experience developing AI/ML applications, including LLM-powered applications, applied machine learning solutions, data-intensive applications, intelligent automation capabilities, or agentic systems.

  • Strong proficiency with Python and experience with AI/ML or deep learning frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Semantic Kernel, or similar tools.

  • Experience working with model APIs, prompt orchestration, retrieval-augmented generation, evaluation approaches, observability tools, cloud platforms, containers, or orchestration technologies.

  • Understanding of system design, application architecture, model and framework tradeoffs, experimentation, evaluation, performance optimization, and production deployment considerations for AI systems.

  • Experience building maintainable and well-tested services, APIs, data pipelines, applications, or platforms.

  • Experience with version control, CI/CD, code review practices, documentation, operational monitoring, and production support.

  • Ability to break down business and technical requirements into clear engineering tasks and deliver practical solutions in collaboration with cross-functional partners.

  • Strong communication skills, with the ability to explain technical concepts clearly to engineers, Data Scientists, product partners, and business stakeholders.

  • Ability to work independently on defined workstreams, collaborate effectively with senior technical partners, and contribute to strong engineering practices within the team.

  • Self-driven and results-oriented, with strong ownership, sound judgment, and the ability to move quickly while maintaining high technical standards.

  • Collaborative team player with a commitment to continuous learning, knowledge sharing, and building reliable AI systems that create business value.

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