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Staff Data Engineer

TJX (TJ Maxx)

Staff Data Engineer

TJX (TJ Maxx)

Hyderabad, TS 500081

·

On-site

·

Full-time

·

1w ago

Benefits & Perks

Healthcare

401(k)

Flexible Hours

Learning Budget

Healthcare

401k

Flexible Hours

Learning

Required Skills

Python

SQL

Azure

Git

Machine Learning

Data Engineering

TJX Companies

At TJX Companies, every day brings new opportunities for growth, exploration, and achievement. You’ll be part of our vibrant team that embraces diversity, fosters collaboration, and prioritizes your development. Whether you’re working in our four global Home Offices, Distribution Centers or Retail Stores—TJ Maxx, Marshalls, Homegoods, Homesense, Sierra, Winners, and TK Maxx, you’ll find abundant opportunities to learn, thrive, and make an impact. Come join our TJX family—a Fortune 100 company and the world’s leading off-price retailer.

Job Description:

What you’ll discover

  • Inclusive culture and career growth opportunities

  • Global IT Organization which collaborates across U.S., Canada, Europe, Australia and India, click here to learn more

  • Challenging, rewarding, collaborative, and team-based environment

  • Modernized tools and technology

What you’ll do

The Enterprise Data & Analytics organization has multiple product teams aligned to business domains. This individual will be a key contributor to the AI enablement team whose goal is to drive responsible adoption and deployment of AI capabilities and solutions at TJX. The AI enablement team is designing and implementing a AI technology ecosystem to support the organization and is also supporting the incubation and implementation of innovative POV efforts.

We are seeking a highly skilled and ambitious Engineer to join AI enablement team. The ideal candidate will have extensive experience in partnering, developing and deploying AI solutions across a large enterprise. This role will work closely with various stakeholders to ensure business value is understood and implemented in ways to quickly achieve this value.

You’ll be a strong fit for this role if you have experience in Data Engineering whether on any cloud platform (Azure, AWS, GCP) or within data‑warehouse environments (Like Snowflake, Databricks) on top of GenAI implementation.

Key Responsibilities:

  • Design, develop, test and deploy AI solutions using Azure AI services to meet business requirements.

  • Train, fine-tune, and evaluate AI models, including large language models (LLMs), ensuring they meet performance criteria and integrate seamlessly into new or existing solutions.

  • Develop and integrate APIs to enable smooth interaction between AI models and other applications, facilitating efficient model serving.

  • Collaborate effectively with cross-functional teams, including data scientists, software engineers, and business stakeholders, to deliver comprehensive AI solutions.

  • Optimize AI and ML model performance through techniques such as hyperparameter tuning and model compression to enhance efficiency and effectiveness.

  • Monitor and maintain AI systems, providing technical support and troubleshooting to ensure continuous operation and reliability.

  • Create comprehensive documentation for AI solutions, including design documents, user guides, and operational procedures, to support development and maintenance.

  • Stay updated with the latest advancements in AI, machine learning, and cloud technologies, demonstrating a commitment to continuous learning and improvement.

  • Design, code, deploy, and support software components, working collaboratively with AI architects and engineers to build impactful systems and services.

  • Lead medium to large initiatives, prioritizing and assigning tasks, providing guidance, and resolving issues to ensure successful project delivery.

What you’ll need

Enterprise Data & Analytics thrives on strong relationships with our business and IT partners and working diligently to address their needs which support TJX growth and operational stability. On this tightly knit and fast-paced team you will be constantly challenged to stretch and think outside the box. We are looking for someone who embraces the use of emerging technology to design, build, deploy, and govern AI solutions.

Key Responsibilities:

  • Design, develop, and deploy AI/ML and GenAI solutions in a cloud-native (Azure) environment.

  • Build and operationalize end‑to‑end MLOps pipelines including model training, deployment, monitoring, and versioning using tools such as Azure ML, MLflow, Databricks, and Azure DevOps/GitHub.

  • Implement RAG pipelines, prompt engineering, guardrails, and LLMOps best practices for scalable GenAI applications.

  • Develop secure, scalable APIs and integrate with Azure AI Services (Document Intelligence, Search, Vision, Speech).

  • Work with vector databases (FAISS, Weaviate, Pinecone, pgvector, Azure Cognitive Search) for embeddings and retrieval workflows.

  • Collaborate in an Agile/Scrum environment, including requirements gathering, design, testing, and documentation using Jira and Confluence.

  • Ensure AI solutions follow security best practices such as encryption, access control, and safe‑deployment principles.

  • Apply ethical AI principles including bias detection, responsible ML, and fairness.

  • Troubleshoot issues using monitoring tools like App Insights, Azure Monitor, and Splunk.

  • Stay current on the latest developments in GenAI, LLMs, NLP, and multimodal AI.

Required Qualifications:

  • Bachelor degree in computer science, Engineering, or a related field.

  • 5+ years of hands-on AI/ML development experience with production deployments.

  • Strong proficiency in Python, SQL, and modern software engineering practices.

  • Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, and core Azure cloud services.

  • Expertise in version control (Git), CI/CD pipelines for ML, and cloud DevOps workflows.

  • Practical experience with data engineering tools and scalable data processing (e.g., Databricks, PySpark).

  • Strong communication, analytical thinking, and problem-solving abilities.

  • Knowledge of security best practices for AI systems and responsible AI considerations.

Preferred Qualifications:

  • Experience with LLM application frameworks such as Lang Chain, Semantic Kernel, and Llama Index.

  • Experience with multimodal AI use cases and advanced GenAI workloads.

  • Knowledge of feature stores and ML operations tools such as Feast, Tecton, Evidently, or Why Labs.

  • Familiarity with vector search implementation at scale.

  • Ability to design guardrails and content safety workflows for LLM applications.

  • Strong passion for continuous learning, research, and staying ahead of GenAI trends.

In addition to our open door policy and supportive work environment, we also strive to provide a competitive salary and benefits package. TJX considers all applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, gender identity and expression, marital or military status, or based on any individual's status in any group or class protected by applicable federal, state, or local law. TJX also provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law.

Address:

Salarpuria Sattva Knowledge City, Inorbit Road

Location:

APAC Home Office Hyderabad IN:

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About TJX (TJ Maxx)

TJX (TJ Maxx)

TJX Companies operates off-price retail chains including TJ Maxx, Marshalls, and HomeGoods, selling brand-name apparel and home goods at discounted prices. The company sources merchandise from manufacturers' excess inventory and operates over 4,800 stores across multiple countries.

10,001+

Employees

Framingham

Headquarters

Reviews

3.9

1 reviews

Work Life Balance

3.0

Compensation

1.5

Culture

3.5

Career

2.0

Management

3.0

25%

Recommend to a Friend

Pros

High customer service ratings

Friendly customer relationships

Opportunities for additional income

Cons

Low wages

Limited income potential

Concerns about commission-based opportunities

Interview Experience

3 interviews

Difficulty

2.3

/ 5

Duration

21-35 weeks

Offer Rate

33%

Experience

Positive 0%

Neutral 33%

Negative 67%

Interview Process

1

Phone Screen

2

Hiring Manager Interview

3

Team Member Interview