Senior Software Engineer

The Senior Software Engineer builds and supports software systems that enable AI-driven capabilities in products and internal platforms. This role focuses on developing reliable services, APIs, and workflows that integrate machine learning and generative AI (where applicable) into real-world applications. The engineer works closely with AI/ML engineers, data engineers, and product partners to deliver features from design through production support. Key Responsibilities Develop backend services and APIs that integrate AI/ML capabilities into applications (e.g., inference endpoints, orchestration services, workflow automation). Implement business logic around AI outputs, including validation, confidence handling, fallback behaviors, and human-in-the-loop patterns where needed. Build integration layers to connect AI services with enterprise systems and data sources. Own delivery of highly complex features/components with limited guidance: break down tasks, estimate effort, and deliver on schedule. Write clean, maintainable code with appropriate abstractions and documentation. Build robust testing (unit/integration) and ensure features meet performance, reliability, and security expectations. Instrument services with logging, metrics, and tracing; support production monitoring and incident triage. Troubleshoot issues across environments and participate in on-call/operational support rotations as applicable. Apply basic responsible AI practices logging, transparency, and guardrails based on established team standards. Required Qualifications Bachelor s degree in Computer Science, Engineering, or related field (or equivalent experience). 5 7 years of professional software engineering experience delivering production applications/services. Proficiency in at least one modern language such as Python, C#, etc.. Experience building APIs/services , working with databases, and shipping features via CI/CD pipelines. Solid understanding of software engineering fundamentals: data structures, debugging, testing, and code quality. Experience supporting AI or ML-enabled applications (e.g., integrating inference services, building orchestration around model outputs). Familiarity with LLM application patterns (prompt orchestration, RAG basics, tool/function calling) and evaluation concepts. Nice to Have Experience with cloud platforms (e.g., Azure/AWS/GCP ) and containerization (Docker/Kubernetes). Exposure to event-driven systems (queues/streams) and observability tooling. Experience with basic front-end development or building AI-assisted UX flows. Core Skills Backend Engineering: REST APIs, services, async processing, microservice patterns Software Quality: unit/integration testing, CI/CD, code reviews, documentation Operations: logging/metrics/tracing, performance tuning, incident triage AI Integration (preferred): model inference integration, orchestration, guardrails/fallbacks Data Fundamentals: SQL basics, data contracts, working with structured/semi-structured data Minimum Qualifications Doctorate (Academic) Degree and 0 years related work experience; Masters Level Degree and related work experience of 3 years; Bachelors Level Degree and related work experience of 5 years