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Target
Target

Retail company.

Principal Engineer - Target India

직무리테일
경력Staff+
위치Bengaluru, India
근무오피스 출근
고용정규직
게시2개월 전
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About us: Target is an iconic brand, a Fortune 50 company and one of America’s leading retailers. Target Technology Services is the behind-the-scenes powerhouse that fuels Target’s commitment to cutting-edge innovation delivering incredible value to guests online and in stores through a strong technology framework and high-performing teams.

Target Tech Overview: Every time a guest enters a Target store or browses Target.com, they experience the impact of Target’s investments in technology and innovation. We are the technologists behind one of the most loved retail brands, delivering joy to millions of our guests, team members, and communities.Our global in-house technology team of more than 5,000 engineers, data scientists, architects and product managers strive to make Target the most convenient, safe and joyful place to shop. We leverage open-source software to adapt and build best-in-class technology for our team members and guests and we do so with a focus on experimentation and continuous learning.

About Pyramid: Merchandising is a Portfolio within Target Tech that provides reliable data core to our enterprise retail operations, including foundational data and aggregation services at scale for retail and commerce platforms. We deal with data around Pricing, Promotions, Item, Supplier, Owned Brand, Merch Planning, Space Presentation & Transitions (SPT) & Intelligence Automation.

Job description

As a Principal Engineer in Merchandising (SPT), you are a thought leader and trusted partner to product and technology teams defining solutions to highly complex business and technology problems. You solve problems impacting multiple lines of business and technologies, define architecture strategies for new or evolving capabilities, align partners to those strategies, and drive delivery of the architectural solutions that evolve Merchandising products. You apply your abilities to solve large abstract problems, see the big picture, take partners, and drive outcomes as you define strategies to lead Merchandising into the future. Your strategic visioning directly contributes to Target’s business and technology.

SPT is a foundational growth enablement platform translating merchant intent into in-store execution. As Target accelerates AI-first ways of working and scale, SPT technology is at an inflection point. In this role, you will champion Agentic capabilities not only for SPT outcomes but by shaping reusable Agentic patterns, governance, and enablers that can scale across the broader Merchandising portfolio.

You clearly and concisely describe problems, opportunities, and vision in ways product and engineering partners and executive leadership understand. You provide clear guidance for teams to implement solutions and other PEs to understand and articulate vision to their partners as needed. You are a curious, active learner who seeks out and understands emerging technology and its implications to Target. You partner with your engineering team to drive proof-of-concepts as needed and clearly communicate findings to the organization. You also embody industry best engineering practices and create a culture for learning & growth.

You possess a broad understanding of Target’s technology, infrastructure, security and compliance landscapes and apply that as you define solutions and guide teams during implementation. You influence engineers to understand and follow practices, standards, and guidelines established to govern solutions. You are a valued leader and team member who listens and understands other viewpoints, makes the right connections, and drives results that matter enabling Target to deliver exceptional experiences to guests and team members. You are expected to mentor, and coach leads into next in line PEs.

About you:

  • Ability to own the end-to-end technical strategy for microservices based and AI/agentic capabilities, including roadmap, reference architectures, platform decisions, and adoption plan across multiple teams

  • Ability to architect cloud-native microservices and event-driven systems using Kafka and distributed patterns (resiliency, scalability, observability, performance, cost optimization)

  • Hands-on experience with core backend stack(Java, Kotlin, Python, etc) and data stores (PostgreSQL, MongoDB, Cassandra, etc) in high-scale environments with proficiency designing APIs and integrations for enterprise platforms.Experienced in search and retrieval architectures leveraging Elastic Search and vector/hybrid retrieval patterns

  • Experienced in designing Agentic orchestration & Flows using Lang Graph, Google ADK, etc, including routing, state management, retries, idempotency, and human-in-the-loop controls anddelivering production LLM solutions (RAG, tool/function calling via MCP) with measurable quality, latency, and cost outcomes

  • Ability to establish evaluation and quality gates for LLM/agentic systems (golden datasets, automated regression, online monitoring)

  • Experienced in implementing safety and governance controls (prompt injection defenses, data access controls, safe tool execution, auditability, PII handling)

  • Ability to influence end-to-end product experience by collaborating with frontend teams (ReactJS) and UX/product partners to deliver intuitive AI-assisted workflows

  • Experienced in platform enablement and adoption at scale, including developer experience, documentation/playbooks, and migration strategies from legacy patterns

  • Ability to lead cross-team technical direction through architecture reviews, ADRs, stakeholder alignment, and mentorship of senior engineers/tech leads

  • Strong written and verbal communication skills and able to communicate technical solutions to technical and non-technical partners

  • Track record of driving outcomes in self-directed manner. Stay current with new and evolving technologies via formal and self-directed education

  • Develop **whitepapers, patents,**contribution to open-source community, attend/present in conferences

  • Retail domain experience applying AI/agentic capabilities to real operational workflows and exception handling will be a plus

  • Demonstrated experience of 12+ years in software engineering with3+ years in architecture/technical leadership

  • Experienced in delivering 2+ years of production AI/ML, LLM-enabled, Agentic AI systems with LLMOps and MLOps practices
    Life at Target- https://india.target.com/

Benefits- https: //india.target.com/life-at-target/workplace/benefits

Culture- https: //india.target.com/life-at-target/belonging

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Target 소개

Target

Target

Public

Target Corporation, doing business as Target, is an American retail corporation headquartered in Minneapolis, Minnesota, United States. Target operates retail stores. It is the eighth-largest retailer in the United States and is a component of the S&P 500 Index.

10,001+

직원 수

Minneapolis

본사 위치

$78B

기업 가치

리뷰

10개 리뷰

3.7

10개 리뷰

워라밸

3.2

보상

2.8

문화

4.1

커리어

3.5

경영진

4.0

68%

지인 추천률

장점

Friendly coworkers and great team environment

Flexible scheduling and hours

Supportive and approachable management

단점

Limited or insufficient hours for part-time staff

Long hours and high stress during peak/holiday seasons

Low pay and non-competitive compensation

연봉 정보

50개 데이터

Junior/L3

Mid/L4

Lead

Director

Junior/L3 · Decision Sciences Analyst

1개 리포트

$104,000

총 연봉

기본급

$80,000

주식

-

보너스

-

$104,000

$104,000

면접 후기

후기 46개

난이도

4.0

/ 5

소요 기간

21-35주

합격률

20%

경험

긍정 65%

보통 21%

부정 14%

면접 과정

1

Recruiter Screen

2

ML Coding

3

ML System Design

4

Research Discussion

5

Team Interviews

자주 나오는 질문

ML fundamentals

Design an ML system

Research paper discussion

Statistical concepts