Platform Engineer III

As the Data & AI Lead Engineer, you will bridge the gap between complex data engineering and cutting-edge artificial intelligence. You will architect, build, and scale robust data pipelines while leading the integration of Machine Learning (ML) and Large Language Model (LLM) workflows into our core products, Architecture & Core Engineering

• Data & AI Infrastructure: Design, implement, and maintain scalable, fault-tolerant data pipelines (ETL/ELT) and MLOps frameworks to support real-time and batch processing.
• AI Integration: Architect and deploy production-grade ML models, Generative AI applications, and Retrieval-Augmented Generation (RAG) systems.
• Data Modeling: Establish best practices for data warehousing, lakehouses, and vector databases to support both analytical and operational AI needs.
• Performance Tuning: Optimize distributed computing workloads and model inference costs for high throughput and low latency.

1. Leadership & Strategy

• Team Mentorship: Guide, code-review, and mentor a team of data and ML engineers, fostering a culture of technical excellence and continuous learning.
• AI Roadmap: Partner with leadership to define the company’s AI capabilities, evaluating new frameworks, tools, and SaaS providers.
• Governance & Compliance: Define data governance, security policies, and ethical AI guidelines (e.g., data privacy, bias mitigation, model drift tracking).

Civil Engineering, Artificial Intelligence (AI), Data Management, Machine Learning, Bridge Building, Modeling Languages, Database Extract Transform and Load (ETL), Data Modeling, Data Warehousing, Best Practices, * Programming: Mastery of Python and solid proficiency in SQL, Scala, or Java.

• Data Engineering: Deep experience with modern data stack tools like Spark, Databricks, Snowflake, dbt, and orchestrators like Apache Airflow.
• AI & Machine Learning: Practical experience deploying frameworks like PyTorch or TensorFlow, alongside GenAI tools like LangChain, LlamaIndex, and vector databases (e.g., Pinecone, Milvus, or Chroma).

Cloud & DevOps: Strong hands-on experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes), specifically tailored for MLOps

Other Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• 6+ years of professional experience in data engineering or software engineering.
• 2+ years of experience leading technical teams or acting as a principal/lead engineer.
• Proven track record of taking AI/ML models out of notebooks and successfully embedding them into production-grade software.

Information at a Glance

Why HCLTech?

At HCLTech, youll supercharge your potential. Youll find your career. And youll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 230,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2026 totaled $14.8 billion.