Senior Software Development Engineer-AI

Delta Tech Hub; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Delta Tech Hub is seeking a Senior Software Developer (G6) with strong backend and full-stack capabilities. You will design, build, and optimize scalable solutions using Java, Spring Boot, and React while leading microservices and cloud-native initiatives.

You will mentor developers, drive engineering excellence, and implement AI-enabled features within a secure, observant environment. You will collaborate with product managers, architects, and AI practitioners to deliver enterprise-grade AI

Qualifications

• Strong background in backend and full-stack development.
• Proven experience with Java and Spring Boot.
• Experience with React frontend.
• Cloud-native, microservices, and DevOps practices.
• Security and performance-focused coding standards.
• Mentoring and technical leadership.
• Familiarity with AI/ML integration.

Responsibilities

• Design, develop, and optimize scalable applications.
• Lead microservices, REST APIs, and cloud-native solutions.
• Own end-to-end delivery from design to production support.
• Mentor developers and promote best practices in coding, performance, and security.
• Design and implement AI-enabled capabilities leveraging AI platforms and frameworks.
• Collaborate with product managers, architects, data engineers, and AI practitioners to deliver AI solutions.
• Collaborate with cross-functional teams to deliver high-quality solutions.
• Ensure adherence to coding standards, security, and compliance.

Skills

Java

Spring Boot

React

Cloud-native engineering

AI/ML integration

Microservices architecture

Security best practices

Tools

AWS

Docker

Kubernetes

Job description

We are seeking a highly skilled Senior Software Developer (G6) with strong expertise in backend and full-stack development, cloud-native engineering, AI/ML and microservices architecture. The candidate will play a key role in designing, developing, and optimizing scalable solutions, mentoring developers, and driving engineering excellence across the team while ensuring high standards of quality, security, and performance.

Responsibilities include, but are not limited to:

• Design, develop, and deliver scalable, secure, and high-performance applications using modern programming languages and frameworks (Java, Spring Boot, React, etc.).
• Lead development of microservices, REST APIs, and cloud-native solutions aligned with enterprise architecture patterns.
• Own end-to-end delivery including design, coding, testing, deployment, and production support.
• Provide technical leadership by reviewing code, mentoring developers, and driving best practices in coding, performance, and security.
• Design and implement AI-enabled application capabilities leveraging enterprise-approved AI platforms, LLMs, and intelligent automation frameworks.
• Lead the development of AI-powered features such as conversational interfaces, intelligent search, recommendation systems, workflow automation, and knowledge-driven applications.
• Collaborate closely with product managers, business teams, architects, data engineers, and AI practitioners to define and deliver business-focused AI solutions.
• Collaborate closely with product managers, business teams, and cross-functional engineering teams to deliver high-quality solutions.
• Ensure adherence to coding standards, responsible AI principals, security frameworks, and compliance requirements (Sonar, Veracode, etc.).
• Familiarity with AWS AI/ML services such as Amazon SageMaker, Bedrock, and AgentCore.
• Demonstrated experience using AI-assisted development tools (e.g., GitHub Copilot, Claude, Kiro) to accomplish tasks such as generating and reviewing code, writing and maintaining tests, creating documentation, and debugging, with the judgment to validate and own AI-generated output.
• Understanding prompt engineering, AI workflows, or model integration patterns.
• Experience working with generative AI or LLM-based solutions is highly desirable.
• Knowledge of AI Agent architectures, intelligent workflow automation, and modern AI application patterns.
• Understanding of ontology, semantic models, metadata-driven architectures, knowledge graphs, and enterprise knowledge management concepts.
• Understanding AI evaluation techniques, prompt engineering, model selection, and AI application observability.
• Knowledge of Responsible AI principles include fairness, transparency, explainability, privacy, accountability, and compliance
• Monitor, troubleshoot, and optimize applications using observability tools (CloudWatch, Dynatrace, Sumo Logic).
• Participate in production support, incident management, RCA, and on-call rotations with ownership mindset.
• Contribute to architecture discussions and influence technical decisions with scalable and reusable solutions.