Sgunitedjobs- Senior AI Engineer

Job Description & Requirements Make an Impact by: Build end-to-end workflows using AI, software and automation solutions Develop and maintain integration of AI solutions with enterprise systems via APIs, MCP, and related frameworks. Work with architects to understand requirements and define solution approaches, while partnering with software engineers for system integration. Enhance and maintain user interfaces for usability and continuous improvement. Design hybrid solutions combining backend, frontend, LLM, prompting, potentially RPA for human-in- the-loop workflows Maintain middleware components including SSO, authentication, and authorization mechanisms. Monitor production AI solutions, track KPIs, and proactively resolve performance or reliability issues. Implement security best practices, establish fallback/backup strategies, and mitigate potential risks in AI solutions. Maintain and enhance existing solution with right and relevant AI capabilities across Enterprise, Consumer, IT, Networks and Corporate Functions domain. Support and optimize the marketplace recommender system, ensuring updated offers and business rules are integrated smoothly. Monitor, troubleshoot, and improve production pipelines, backend and frontend application and AI services for reliability, performance, and scalability. Stay up to date with the latest advancements in AI/agentic AI and conduct applied research to enrich internal capabilities. Apply software engineering standards, including modular code design, reproducibility, and rigorous testing. Faced new problems which does not exist a tested approach and requires some level of R&D Balancing between process and approval management vs project timelines Skills for Success: Bachelor’s or Master’s degree in Computer Science, Engineering, Data, AI/ML, or related field. 3-5 years of proven experience developing and deploying software and AI solutions, with exposure to agentic AI frameworks. Proficient in Python, and TypeScript/nodejs, SQL, etc Hands-on experience with LangChain, LangGraph, or similar AI frameworks. Good knowledge in LLM integration and orchestration. Knowledge in prompt engineering. Experience with API development and integration (RESTful, gRPC, MCP a plus). Knowledge of middleware systems, including SSO and access control (OAuth2, JWT, etc.). Familiar with version control (GitHub, GitLab, Bitbucket). Exposure to cloud platforms (Azure, AWS, GCP preferred). Passion for applied R&D, staying ahead of AI advancements, and bringing innovative ideas into production. Strong problem-solving ability, attention to detail, and ability to collaborate effectively across teams. Comfortable working in a cross-functional team (Software/AI engineers, data platform, business users). Experience in building secure, enterprise-grade integrations.