Senior Software Engineer

Job Description

You will serve as a Technical Authority for AI engineering, providing deep technical expertise across AI architecture, engineering, and delivery. You will drive technical direction for complex AI-powered products and platforms. You will provide clarity on ambiguous AI problems through research, experimentation, prototyping, and data-driven technical recommendations. You will evaluate emerging AI technologies, models, frameworks, and architectural patterns and recommend where and how they should be adopted. You will establish reusable AI engineering patterns, reference architectures, frameworks, and good practices. You will drive architecture and design reviews for complex AI systems. You will influence technical decisions across multiple engineering teams without requiring direct organizational authority. You will become a trusted technical point of contact for complex AI engineering and delivery questions. You will drive the architecture and engineering of a Unified AIOps Platform, bringing currently independent tools, applications, AI agents, skills, workflows, and automation capabilities into a cohesive and extensible ecosystem. You will define common orchestration, integration, agent-to-agent communication, identity, data, observability, and governance patterns that enable capabilities to work seamlessly together. You will establish a plug-and-play architecture where new agents, skills, tools, and services can be easily onboarded, discovered, orchestrated, and reused across scenarios. You will remain deeply hands-on in designing and building the platform while driving technical alignment across contributing teams and enabling the organization to evolve from siloed AI solutions to a unified, scalable AIOps ecosystem. Bachelor's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 10+ years of hands-on software engineering experience, with deep expertise in designing, developing, and delivering enterprise-scale, cloud-native applications and distributed systems. Proven experience building production-grade AI solutions, including Generative AI, LLMs, AI Agents, Agentic AI, multi-agent systems, RAG, semantic search, vector databases, and workflow orchestration. Good full-stack engineering expertise across frontend, backend, APIs, microservices, cloud platforms, data engineering, and modern application architectures using technologies such as C#, .NET, Python, React/Angular, TypeScript, REST, GraphQL, and Azure. Hands-on experience across the AI lifecycle, including model selection, fine-tuning, evaluation, prompt engineering, inference optimization, safety validation, and production deployment of AI solutions. Demonstrated ability to build secure and responsible AI systems, implementing grounding, hallucination mitigation, guardrails, Responsible AI practices, security, governance, observability, and operational excellence. Good expertise in cloud-native architecture and platform engineering, including scalable microservices, event-driven architectures, authentication, authorization, CI/CD, telemetry, monitoring, reliability, performance optimization, and cost-efficient production operations. Good troubleshooting and problem-solving skills, with the ability to diagnose and optimize complex AI systems across models, prompts, agents, orchestration layers, data pipelines, and distributed services. Demonstrated technical leadership as a Sr. Individual Contributor (IC), influencing architecture, establishing engineering standards, mentoring engineers through design and code reviews, and driving technical strategy across multiple teams. Good collaboration and communication skills, with experience partnering with Product Managers, Architects, Applied Scientists, Security teams, and executive stakeholders, while representing the organization in technical architecture reviews, AI engineering forums, and cross-functional initiatives. Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. Understanding of Responsible AI, compliance, privacy, governance, and enterprise security requirements. Experience designing agent evaluation, observability, quality measurement, and reliability frameworks for AI-powered solutions. Experience working with networking, infrastructure, telemetry, or large-scale operational systems. Experience building enterprise-scale AIOps, operational intelligence, monitoring, and observability.