Senior AI Engineer

Company Summary

A leading telecommunications and technology enterprise is undertaking a major strategic transformation to embed artificial intelligence and data analytics into the core of its business. Through a dedicated central AI and data organization, the company is focused on scaling agentic AI, building enterprise-wide AI literacy, and augmenting human capability across its consumer, enterprise, IT, network, and corporate divisions. They foster an agile, innovation-driven culture that puts human potential at the heart of technology evolution.

Roles & Responsibilities

• Solution Design & Implementation: Develop end-to-end AI workflows, agentic AI solutions, and hybrid systems combining front-end/back-end software, LLMs, prompt engineering, and automation tools for human-in-the-loop processes.
• System Integration & Architecture: Collaborate with Solution Architects and Lead Engineers to integrate AI solutions into enterprise ecosystems using APIs, Model Context Protocol (MCP), and middleware components (including SSO, OAuth2, and JWT).
• Full-Stack Development: Maintain and continuously enhance user interfaces for usability while applying modular, high-standard software engineering practices across back-end pipelines and front-end applications.
• Operations & Monitoring: Monitor production AI services and recommendation engines, track KPIs, ensure high availability, and proactively resolve reliability, scalability, or performance issues.
• Security & Risk Mitigation: Enforce security best practices, build enterprise-grade integrations, establish fallback strategies, and manage risk across production systems.
• Applied R&D & Innovation: Tackle novel, untested problems through applied R&D, stay current with advancing AI/agentic frameworks, and bring continuous improvements into live enterprise environments.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data, AI/ML, or a related field.
• 3–5 years of hands-on experience in software development and AI deployment, with proven exposure to agentic AI workflows and marketplace/recommender systems.
• Languages: Python and SQL.
• AI/ML Frameworks: LangChain, LangGraph, or equivalent agentic and LLM orchestration tools, alongside strong prompt engineering knowledge.
• Integrations & Middleware: RESTful APIs, gRPC, MCP, SSO, OAuth2, and JWT.
• Engineering Tools: Cloud environments (AWS, Azure, or GCP) and Git version control (GitHub, GitLab, Bitbucket).
• Strong balance of operational ownership, R&D curiosity, and problem-solving skills.
• Ability to navigate project timelines alongside governance and process approvals.
• Excellent collaboration skills for working with cross-functional technical and business teams.