AI Platform Engineering (B2B Integration)

Exp: 7+ yrs
Location Option: Chennai - WFO HYBRID
Job Description:
Senior Software Developer – AI Platform Engineering (B2B Integration)
Location: Chennai, India (Hybrid / Remote within India)
Department: Product Development / AI Engineering
Working Model: Agile (Scrum)
Experience: 7 –14 Years
Role Overview
We are looking for a highly motivated Senior Software Developer with strong engineering expertise and practical experience in modern AI technologies.
In this role, you will design and develop enterprise-grade services that combine Java-based microservices, cloud-native architectures, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI-driven workflows.
You will work closely with software engineers, architects, product owners, and platform teams to deliver scalable, secure, observable, and maintainable solutions for global enterprise customers.
This position is ideal for developers who enjoy building production-ready systems and applying AI technologies to solve real-world business and integration challenges.
Key Responsibilities
Platform Development
Design, develop, and maintain enterprise-grade backend services using Java and Spring Boot.
Build scalable microservices and APIs that support AI-enabled platform capabilities.
Develop integrations between internal systems, cloud services, and external AI platforms.
Implement event-driven architectures using Kafka or similar messaging technologies.
Contribute to platform components that support enterprise-scale B2B integration scenarios.
AI Engineering
Develop AI-powered application features using Large Language Models (LLMs).
Implement Retrieval-Augmented Generation (RAG) solutions, semantic search, and knowledge retrieval capabilities.
Design prompt orchestration, context management, and AI workflow logic.
Integrate AI tools, external services, and agent-based workflows into enterprise applications.
Contribute to the implementation of AI governance, guardrails, and responsible AI practices.
Evaluate and adopt emerging AI frameworks, technologies, and engineering approaches.
Cloud & DevOps
Develop and deploy cloud-native applications on modern cloud platforms.
Build and maintain containerized workloads using Docker and Kubernetes.
Contribute to CI/CD pipelines, deployment automation, and release processes.
Support platform scalability, reliability, resilience, and operational excellence.
Engineering Excellence
Implement automated testing strategies including unit, integration, and component testing.
Participate in architecture discussions, design reviews, and code reviews.
Apply software engineering best practices, clean code principles, and design patterns.
Implement observability through logging, metrics, tracing, and monitoring.
Troubleshoot and resolve issues across development, test, and production environments.
Mentor junior team members and contribute to knowledge sharing within the team.
Agile Collaboration
Actively participate in Scrum ceremonies and Agile development activities.
Collaborate with cross-functional teams across engineering, architecture, product management, and operations.
Contribute to continuous improvement initiatives and engineering excellence programs.
Required Technical Skills
Core Backend Engineering
Strong hands-on experience with Java.
Strong experience with Spring Boot and enterprise application development.
Solid understanding of microservice architectures and distributed systems.
Experience designing and developing REST APIs.
Strong SQL and relational database knowledge (PostgreSQL, Oracle, or similar).
Experience with event-driven systems and messaging technologies such as Kafka.
AI & Generative AI
Experience working with AI-assisted development tools such as GitHub Copilot, Claude, or similar solutions.
Experience building applications that leverage Large Language Models (LLMs).
Practical knowledge of Retrieval-Augmented Generation (RAG) architectures.
Understanding of prompt engineering, context management, and AI workflow patterns.
Familiarity with vector databases, embeddings, and semantic search concepts.
Experience with AI application frameworks such as Spring AI, LangChain, LangGraph, or similar.
Cloud & Platform Technologies
Experience with Docker and Kubernetes.
Familiarity with AWS, Azure, or comparable cloud platforms.
Experience with CI/CD pipelines and DevOps practices.
Understanding of cloud-native application design principles.
Software Engineering
Strong understanding of software quality, testing, and maintainability.
Experience with Git-based development workflows.
Knowledge of design patterns and modern software architecture principles.
Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
The following skills are advantageous but not mandatory:
Experience with Agentic AI architectures and AI orchestration frameworks.
Exposure to Model Context Protocol (MCP) or similar tool integration approaches.
Experience with OpenTelemetry and modern observability platforms.
Knowledge of enterprise integration technologies, API management, or B2B integration concepts.
Professional Experience
7 –12 years of professional software development experience.
Strong track record of delivering enterprise-grade backend applications.
Experience developing microservices and cloud-native solutions.
Experience working within Agile software development teams.
Practical experience with AI-enabled applications is highly desirable.
Education
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a related discipline.
Equivalent practical experience will also be considered.

Work arrangement
Hybrid