Senior Java Backend Developer – Data/AI Platforms

Winzons

India

On-site

INR 4,000,000 - 6,000,000

Full time

14 days+

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

Talent Corner HR Services in Bangalore, India is seeking a Senior Backend Developer - Java to design and build scalable backend services using Java 9+ and Spring Boot, crafting robust REST APIs and cloud-native microservices for a data and AI platform.

You will work on large-scale data pipelines, integrate with distributed data systems, and ensure performance, security, and reliability while mentoring juniors and contributing to engineering best practices.

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
10-12 years of professional software engineering experience.
Strong expertise in Java (9+), Spring Boot, REST APIs, and distributed systems.
Experience with AWS cloud services and relational databases.

Responsibilities

Design and build high-performance backend services using Java (9+) and Spring Boot.
Develop and maintain RESTful APIs supporting high-throughput data ingestion and analytics.
Build microservices for large-scale data processing and distributed workloads.
Design APIs for AI model invocation, analytics workflows, and data integration pipelines.
Ensure robust error handling, authentication, validation, and versioning strategies.

Skills

Java (9+)

Spring Boot

REST APIs

Distributed systems

AWS

SQL

Microservices

Data pipelines

Education

Bachelor's or Master's degree

Tools

AWS SDK

Docker

Kubernetes

OpenAPI/Swagger

Job description

Company Name: Talent Corner HR Services

Job Role: Senior Backend Developer - Java

Experience Required: 10-12 Years

Employment Type: Full-Time, Permanent

Location: Bangalore, India

Work Location: In Person

Qualification: Bachelor's or Master's Degree in Computer Science, Engineering, or a related field

Industry: Information Technology / Data & AI Platforms

Job Overview

We are looking for an experienced Senior Java Engineer to help design and build a next-generation enterprise data and AI platform.

In this role, you will design highly scalable backend services using modern Java and Spring Boot, build robust REST APIs, and develop platform services that integrate with distributed data systems, cloud infrastructure, and machine learning workflows.

You will work on systems that manage high-volume data pipelines, large datasets, and cloud-native microservices while ensuring high performance, reliability, and security.

Key Responsibilities

Platform & API Development

Design and build high-performance backend services using Java (9+) and Spring Boot.
Develop and maintain RESTful APIs supporting high-throughput data ingestion, analytics, and AI-driven workflows.
Build microservices that handle large-scale data processing and distributed workloads.
Design APIs that support AI model invocation, analytics workflows, and data integration pipelines.
Implement robust error handling, validation, authentication, and API versioning strategies.

Data Platform Engineering

Design and implement services that manage large-scale structured and unstructured datasets.
Build platform components for:

Data ingestion pipelines
Data transformation and enrichment
Query services for analytics workloads

Integrate with distributed data technologies such as Spark, Delta Lake, Trino, ClickHouse, or similar big data systems.
Design scalable data access layers using JPA/Hibernate, JDBC, or reactive database drivers.
Optimize data models and queries for high-performance workloads.

AI & Intelligent Platform Integration

Build backend services that integrate with machine learning and AI systems.
Design APIs for invoking LLM inference services, vector search, and model pipelines.
Integrate with AI providers such as OpenAI, Anthropic, or AWS Bedrock using secure service layers.
Support RAG architectures through vector database integrations and semantic search services.

Cloud & Distributed Systems

Design cloud-native services deployed on AWS infrastructure.
Develop integrations using AWS SDK for services such as:

S3
ECS / EKS
Lambda
SQS / SNS
EventBridge

Build asynchronous processing pipelines using message queues and event-driven architectures.
Implement scalable deployment pipelines and infrastructure automation.

System Architecture & Engineering Excellence

Design highly scalable and resilient microservice architectures.
Participate in system design reviews and architecture decisions.
Improve system observability through logging, metrics, and distributed tracing.
Mentor junior engineers and contribute to engineering best practices.
Drive improvements in code quality, performance, and reliability.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
10-12 years of professional software engineering experience.
Strong expertise in Java (Java 9+ preferred) and modern Java features.
Extensive experience building Spring Boot microservices.
Deep understanding of REST API design and distributed system architecture.
Strong experience with SQL and relational database design.
Experience working with large-scale data systems or data platforms.
Hands-on experience with AWS cloud services and AWS SDK.

Technical Skills

Programming

Java (9+), modern Java features (Streams, Optional, Records, etc.)

Frameworks

Spring Boot, Spring MVC, Spring Data, Spring Security

Data Technologies

PostgreSQL, MySQL, Oracle, or similar relational databases
Big data technologies such as Spark, Delta Lake, ClickHouse, Trino, or Presto

Cloud & Infrastructure

AWS (S3, ECS, ECR, Lambda, SQS, SNS, EventBridge, IAM)
AWS SDK for Java

API & Integration

REST APIs, JSON/HTTP, OpenAPI/Swagger

AI & Search Technologies

Vector databases (pgvector, Pinecone, OpenSearch)
AI APIs such as OpenAI, Anthropic, AWS Bedrock

DevOps

Docker, CI/CD pipelines, Git-based workflows

Preferred Qualifications

Experience designing large-scale SaaS data platforms.
Experience working with distributed data processing frameworks such as Apache Spark.
Familiarity with data lake technologies such as Delta Lake or Apache Iceberg.
Experience integrating AI or machine learning systems into backend services.
Experience with vector search and semantic retrieval systems.
Knowledge of event-driven architectures and streaming platforms such as Kafka.
Experience with high-performance query engines such as Trino or ClickHouse.
Domain experience in life sciences, healthcare, or pharmaceutical data platforms is a plus.

Soft Skills