Senior Software Development Engineer-AI

How You’ll Help Us Keep Climbing (Overview & Key Responsibilities)

• 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.

What You Need To Succeed (Minimum Qualifications)

• 4–7 years of hands-on experience in software development with strong expertise in Java (preferably Java 21), microservices, and REST APIs.
• Experience with frameworks such as Spring Boot, Quarkus, and Hibernate, and understanding backend/frontend technologies.
• Strong knowledge of cloud-native development on AWS (Lambda, EC2, S3, Kubernetes, Docker, etc.).
• Understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI orchestration concepts.
• Experience integrating enterprise AI services and AI APIs into business applications.
• 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.
• Experience designing and implementing microservices architectures and serverless solutions.
• Proficiency in CI/CD, DevOps practices, and tools (GitLab CI, Maven/Gradle, Nexus, SonarQube, Veracode).
• Strong expertise in relational (Postgres, MySQL, Aurora) and NoSQL databases (DynamoDB, MongoDB, Redis) including query optimization.
• Solid understanding of authentication/authorization mechanisms (OAuth2.0, OpenID Connect, IAM).
• Experience in monitoring, debugging, and troubleshooting production systems.
• Strong commitment to code quality, test automation (JUnit/PyTest), and secure coding pra…