Director, Software Engineering

Jobtailor

Bengaluru

On-site

INR 4,000,000 - 7,000,000

Full time

2 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Jobtailor in Bengaluru seeks a senior engineering leader to build and scale India-wide data platforms and AI/GenAI initiatives. You will guide architecture, mentor teams, and partner with global product and security leaders to deliver scalable, data-driven digital products across time zones.

You will drive DataOps, CI/CD, observability, and responsible AI governance while ensuring platform reliability, security, and efficient costs.

Qualifications

Bachelor’s degree in computer science, engineering, or related field; equivalent practical experience.
15+ years of software engineering experience with leadership across platform, data, analytics, and AI systems.
Experience leading multiple engineering teams delivering enterprise-scale digital platforms in global or multi-regional organizations.
Strong cloud-native, data engineering, and modern software design foundations.
Experience in industrial, manufacturing, automotive, IoT, or connected-equipment environments.
Experience leading AI/ML/GenAI capabilities at enterprise scale.
Leadership in Agile transformation and product-centric ways of working.
Proven success leading large teams in India with global delivery responsibilities.
Deep technical expertise in cloud data platforms (AWS/Azure/GCP), Snowflake, Spark, Kafka, Airflow/Dagster, data modeling, data lake/lakehouse architectures, Python, SQL, and distributed systems.
Experience operationalizing AI/ML and GenAI systems at scale.
Strong communication, cross-cultural collaboration, and executive stakeholder management.

Responsibilities

Lead and scale high-performing engineering teams across Data Platform, Data Engineering, Analytics, and AI/GenAI in India.
Provide technical leadership, architectural oversight, and mentorship.
Partner with global leaders to deliver digital products across time zones.
Drive delivery of data-centric products, platforms, APIs, and ML/GenAI solutions.
Establish CI/CD, DevOps, observability, secure coding, and DataOps practices.
Architect scalable data platforms and govern data lake/lakehouse initiatives.
Oversee batch/streaming pipelines with Spark, Kafka, Airflow, and cloud-native tools.
Champion Responsible AI, governance, and cost optimization.
Represent India engineering in global forums and influence strategy.

Skills

Leadership

Cloud-native architectures

Data platforms

AI/GenAI

Python

SQL

Snowflake

Spark

Kafka

Airflow

DevOps

DataOps

Communication

Education

Bachelor’s degree in CS/Engineering

Tools

AWS

Azure

GCP

Dagster/Dagster-like tooling

Job description

Build, scale, and lead high-performing engineering teams in India across Data Platform, Data Engineering, Data Solutioning, Analytics, and AI/GenAI
Attract, grow, and retain engineering talent and build succession pipelines
Provide technical leadership, architectural oversight, and mentorship
Partner with global Product, Architecture, Security, and Engineering leaders to deliver digital products
Ensure seamless integration and delivery across time zones with U.S. and global teams
Drive delivery of data-centric digital products, platforms, APIs, and ML/GenAI solutions
Establish CI/CD, DevOps, automated testing, observability, secure coding, reusable components, and engineering standards
Architect and evolve scalable Snowflake-based data platforms for telematics, IoT, asset health, services, and analytics
Lead data lake zones, optimization, ingestion frameworks, governance, and cost management
Oversee batch and streaming data pipelines using Spark, Kafka, Airflow, and cloud-native tools
Establish DataOps practices, data quality automation, versioned pipelines, and pipeline observability
Enable governed, self-service analytics, semantic models, KPIs, dashboards, and insights
Lead ML/AI pipelines including training, inference, feature stores, monitoring, and lifecycle governance
Drive GenAI innovation through RAG-based solutions, vector databases, agentic workflows, and LLM integration
Champion Responsible AI practices, governance, and risk frameworks
Ensure platform reliability, scalability, security, regulatory compliance, and cost optimization
Set engineering strategy, priorities, roadmaps, and measurable outcomes
Build and mentor engineering leaders and foster ownership, trust, inclusion, and continuous learning
Represent the India engineering organization in global forums and influence strategy and decisions

Requirements

Bachelor's degree in computer science, Engineering, or a related field, or equivalent practical experience
15+ years of software engineering experience
Significant leadership across platform, data, analytics, and AI systems
Experience leading multiple engineering teams delivering enterprise-scale digital platforms within large, global or multi-regional organizations
Strong foundation in cloud-native architectures, data engineering, and modern software design
Experience in industrial, manufacturing, automotive, IoT, or connected-equipment environments
Exposure to telemetry, edge computing, digital twins, or predictive maintenance solutions
Experience leading AI, ML, or GenAI engineering capabilities at enterprise scale
Leadership in Agile transformation and product-centric ways of working
Proven success leading large-scale engineering teams in India, with global delivery responsibilities
Deep technical expertise in cloud-based data platforms (AWS/Azure/GCP), Snowflake, Spark, Kafka, Airflow or Dagster, data modeling, data lake/lakehouse architectures, Python, SQL, and distributed systems
Experience operationalizing AI/ML and GenAI systems at scale
Strong communication, cross-cultural collaboration, and executive stakeholder management

Core Competencies

Demonstrates expertise in building and leading high-performing engineering teams focused on data platforms, AI, and digital product delivery. Proficient in cloud-native architectures, data engineering, and implementing CI/CD and DataOps practices to drive innovation and operational excellence.

Highest-signal resume keywords