Engineering Manager

Smart Ship Hub; Pune District; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Smart Ship Hub is seeking a senior engineering leader in Pune to architect and guide the development of scalable, AI-powered enterprise systems. You will mentor engineers, drive microservices architecture, and oversee data pipelines and modern AI tooling.

The role requires hands-on design work, strong communication with stakeholders, and delivery through Agile SDLC practices. Experience with cloud-native stacks and large-scale systems is essential.

Qualifications

• 10–14 years of software development experience.
• 3+ years of engineering manager / technical leadership experience.
• Strong communication, stakeholder management, and presentation skills.

Responsibilities

• Lead and mentor a team of engineers while remaining hands-on with architecture, system design, and development.
• Architect and build scalable microservices-based platforms and AI-enabled enterprise products.
• Design and deliver high-performance, high-availability systems capable of scaling to large workloads.
• Drive development of AI-powered applications, including agentic systems, LLMs, and RAG-based solutions.
• Collaborate with product and business teams to translate requirements into robust technical solutions.
• Ensure delivery using Agile sprint processes and structured SDLC practices.
• Establish engineering best practices around code quality, testing, architecture documentation, and observability.
• Guide the team in adopting modern AI developer tools and automation to enhance productivity.
• Drive architecture decisions for data pipelines, big data platforms, and distributed systems.

Skills

Team leadership

Architectural skills

System design

Communication

Stakeholder management

Presentation skills

Agile

SDLC

DevOps

Tools

Docker

Kubernetes

Nginx

AWS

GCP

Kafka

Redis

RabbitMQ

Job description

Responsibilities

• Lead and mentor a team of engineers while remaining hands-on with architecture, system design, and development.


• Architect and build scalable microservices-based platforms and AI-enabled enterprise products.


• Design and deliver high-performance, high-availability systems capable of scaling to large workloads.


• Drive development of AI-powered applications, including agentic systems, LLMs, and RAG-based solutions.


• Collaborate with product and business teams to translate requirements into robust technical solutions.


• Ensure delivery using Agile sprint processes and structured SDLC practices.


• Establish engineering best practices around code quality, testing, architecture documentation, and observability.


• Guide the team in adopting modern AI developer tools and automation to enhance productivity.


• Drive architecture decisions for data pipelines, big data platforms, and distributed systems.

Requirements

• 10-14 years of software development experience.


• 3+ years of engineering manager / technical leadership experience.


• Strong communication, stakeholder management, and presentation skills.

Backend and Frontend

• Strong hands-on experience with Java, Node.js, React.js, and TypeScript.

AI / LLM and Agentic Systems

• Experience building AI-powered enterprise systems, including the development of agentic AI systems, the implementation of LLM-based solutions, and the development of RAG (Retrieval Augmented Generation) pipelines.


• Frameworks and tools such as LangChain, LLaMA, YOLO, Roboflow, and NeMo.


• Experience building production-grade AI models and integrating them into enterprise platforms.

Data Engineering and Big Data

• Strong experience with Python, PySpark, big data ecosystems, and Hadoop.


• Experience building large-scale data processing pipelines and ML data workflows.

Databases

• Strong experience with PostgreSQL and MySQL.


• Knowledge of database sharding, query optimization, and large-scale data storage strategies.

Distributed Systems and Messaging

• Experience with event-driven architecture and messaging platforms: Kafka, Redis, RabbitMQ.

DevOps and Cloud

• Hands-on experience with cloud-native infrastructure: Docker, Kubernetes, Nginx, AWS, and GCP.

Development Practices

• Strong experience working with microservices architecture.


• Experience delivering high-scale, production-grade enterprise systems.


• Experience with Agile development methodologies.


• Familiarity with full SDLC processes: functional specs, architecture documentation, design specs, unit testing, and performance optimization.

AI Developer Productivity Tools

• Experience leveraging modern AI-assisted development tools such as ChatGPT, Cursor, or similar.

Preferred Qualifications

• Experience building AI-driven SaaS platforms.


• Prior experience scaling engineering teams and distributed systems.


• Strong knowledge of system reliability, scalability, and observability.


• Experience integrating AI/ML models into real-time production systems.