AI Software Engineer - Senior

Job Summary The AI Software Engineer Senior is responsible for designing, developing, implementing, and supporting high-quality, scalable software solutions with a focus on enterprise Artificial Intelligence (AI) and agentic systems. This role combines software engineering expertise with modern AI technologies to build secure, reliable, and innovative solutions that address complex business challenges. The incumbent will participate throughout the software development lifecycle, including requirements gathering, solution design, development, testing, deployment, and support. The role requires collaboration with business stakeholders, architects, and cross-functional teams to develop AI-driven products, enterprise integrations, and automation solutions that deliver measurable business value. Key Responsibilities Software Development & Engineering Design, develop, test, deploy, and maintain high-quality software applications in compliance with coding standards, technical design requirements, and software engineering best practices. Develop software solutions by analyzing business requirements, studying systems flow, data usage, and operational processes. Create technical designs, flowcharts, documentation, and implementation plans to support software development initiatives. Evaluate solution feasibility through requirements analysis, problem definition, architecture assessments, and technical design reviews. Participate in all phases of the Software Development Lifecycle (SDLC), including planning, development, testing, deployment, and operational support. Conduct code reviews, support testing activities, and ensure software quality through established engineering practices. AI Solution Development Design and implement enterprise AI solutions using agentic workflows, orchestration frameworks, and large language model (LLM) technologies. Develop multi-agent systems leveraging memory, planning, reasoning, tool usage, and MCP-style interactions. Build production-ready AI workflows that integrate enterprise systems, APIs, data platforms, and business applications. Develop reusable prompts, tools, agents, orchestration pipelines, and AI accelerators. Implement Retrieval-Augmented Generation (RAG) architectures, vector databases, memory systems, and prompt engineering techniques. Enterprise Integration & Automation Integrate AI agents and solutions with enterprise applications such as SAP, SharePoint, ServiceNow, Jira, databases, APIs, and other business systems. Develop secure tool-calling frameworks and data-access mechanisms for AI workflows. Enable AI-powered automation across engineering, manufacturing, operations, safety, and business functions. Design and implement backend services, APIs, orchestration layers, and deployment pipelines. Solution Architecture & Technical Leadership Collaborate with architects and engineering teams to design scalable, secure, and maintainable AI solutions. Define application boundaries, interfaces, integrations, deployment models, and non-functional requirements (NFRs). Optimize AI and software solutions for performance, reliability, scalability, observability, and cost efficiency. Support cloud-native deployments and platform modernization initiatives on AWS and Azure. Promote built-in quality, engineering excellence, and agile development practices across teams. Value Realization & Stakeholder Engagement Partner with business stakeholders to identify high-value AI and automation opportunities. Translate business requirements into technical solutions that drive measurable outcomes. Quantify and communicate business value through productivity improvements, cost savings, quality enhancements, and operational efficiencies. Support pilot implementations and transition proof-of-concepts into production-ready solutions. Innovation & Continuous Improvement Stay current with emerging technologies, AI frameworks, development tools, and industry best practices. Contribute reusable frameworks, templates, standards, and accelerators that improve engineering productivity. Mentor junior engineers and contribute to the development of technical capabilities across teams. Participate in professional development activities and maintain awareness of evolving AI and software engineering trends.ople approach their work while supporting decentralized decision making. Qualifications Education Bachelor's, Master's, or equivalent degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science, or a related technical discipline. Equivalent combination of education and relevant professional experience may be considered. Certifications (Preferred) Cloud certifications (AWS, Azure, or equivalent). AI/ML or Generative AI certifications. Agile, DevOps, or software engineering certifications. Compliance Requirements This position .