IT Head - Data & AI/ML Engineering

Job Description :

Position : HEAD - DATA & AI/ML ENGINEERING

Location : GURGAON

Department : SOFTWARE

Work Mode : 5 Days Work From Office

About :

Company builds enterprise technology platforms that combine location intelligence, large-scale data platforms, and modern cloud-native systems. Our solutions help telecom operators, enterprises, and government organizations leverage data, analytics, geospatial intelligence, and AI-driven systems to solve complex real-world challenges.

We are expanding our engineering leadership and building a Data & AI/ML Engineering organization responsible for developing scalable data infrastructure, machine learning systems, and next-generation AI and GenAI capabilities.

(A) JOB SUMMARY :

We are looking for a Head - Data & AI/ML Engineering to lead the engineering organization responsible for the company's data platform, machine learning systems, and AI/GenAI capabilities.

This role will define the data architecture, ML engineering platforms, and GenAI infrastructure that power intelligent features across multiple enterprise products.

The ideal candidate has strong experience in data engineering, machine learning systems, MLOps, and Generative AI technologies including large language models (LLMs).

(B) JOB DUTIES & RESPONSIBILITY :

1. Data Platform Architecture :

- Design and lead the company's modern data platform architecture.

- Build scalable systems for data ingestion, processing, transformation, and storage.

- Enable reliable and governed data access for analytics, ML models, and AI applications.

2. Data Engineering :

- Build and manage large-scale data pipelines and ETL/ELT systems.

- Implement modern architectures such as :

1. Data Lake

2. Data Warehouse

3. Lakehouse architectures

- Ensure scalability, reliability, and performance of data infrastructure.

3. AI / Machine Learning Engineering :

- Build infrastructure for training, deploying, and monitoring ML models.

- Develop scalable ML pipelines and feature engineering systems.

- Enable product teams to embed AI-powered capabilities into applications.

4. Generative AI & LLM Systems :

- Drive adoption of Generative AI technologies across products.

- Design systems using large language models (LLMs) for intelligent automation and data-driven applications.

- Build architectures for :

1. LLM integration

2. Retrieval-Augmented Generation (RAG)

3. Vector search systems

4. AI agents and copilots

- Evaluate and integrate modern GenAI frameworks and tooling.

5. MLOps & AI Infrastructure :

- Build and maintain infrastructure for :

1. Model training

2. Model versioning

3. Model deployment

4. Monitoring and observability

5. Experimentation frameworks

- Establish MLOps best practices for reliable production ML systems.

6. Data Governance & Quality :

Implement frameworks for :

- Data lineage

- Data quality monitoring

- Access controls

- Compliance and governance

7. AI Adoption Across Products :

Partner with product engineering teams to enable :

- Predictive analytics

- Recommendation systems

- Intelligent automation

- AI-driven decision systems

- GenAI-powered product features

Leadership Responsibilities :

- Build and lead the Data & AI/ML Engineering Pod.

- Mentor data engineers, ML engineers, and AI engineers.

- Define the technical roadmap for data and AI systems.

- Establish best practices for data engineering, ML systems, and AI infrastructure.

- Drive adoption of AI and GenAI capabilities across engineering teams.

(C) TECHNICAL KNOWLEDGE, SKILL-SET & QUALIFICATION :

Data Platforms :

Strong experience in :

- Data pipelines and distributed data processing

- Data lake / lakehouse architectures

- Streaming and real-time data processing

- Large-scale analytics platforms

Machine Learning Systems :

Experience with :

- ML pipelines and feature stores

- Model training and deployment

- ML model monitoring and lifecycle management

Generative AI :

Strong understanding of :

- Large Language Models (LLMs)

- Retrieval-Augmented Generation (RAG)

- Vector databases and embedding systems

- AI agents and copilots

- Prompt engineering and LLM orchestration frameworks

Required Qualifications :

- Experience leading Data Engineering or AI/ML Engineering teams.

- Strong background in large-scale data systems.

- Experience building production machine learning systems.

- Good understanding of Generative AI and LLM-based applications.

- Experience designing scalable data and AI platforms.

Preferred Qualifications :

- Experience building AI-powered enterprise platforms.

- Experience integrating GenAI features into production systems.

- Experience with large-scale data environments.

- Familiarity with geospatial or location intelligence data.

Leadership Expectations :

The Head of Data & AI/ML Engineering will :

- Define the data and AI strategy for the company.

- Build scalable data platforms and AI infrastructure.

- Enable product teams to leverage data, ML, and GenAI capabilities.

- Drive innovation through AI-powered product development.

Why Join Lepton Software :

- Work on large-scale data and AI platforms.

- Build next-generation AI and GenAI capabilities.

- Lead high-impact engineering initiatives.

- Solve complex real-world problems using data and AI.

(ref:hirist.tech)