AI Engineer

Major ResponsibilitiesDesign and develop AI chatbot/AI agent solutions aligned to business use cases and intentsOwn and implement the end-to-end conversation orchestration layer, including decision logic, tool usage, and multi-step interaction flowsIntegrate AI solutions with enterprise systems such as CRM (D365), SAP, contact center platforms (e.g., Genesys), and knowledge basesDevelop and manage APIs, middleware, and data pipelines to support AI interactionsImplement context-aware handoff to live agents (Genesys), ensuring full conversation history and intent propagation for seamless customer experienceCollaborate with business analysts, vendors, and internal teams to ensure accurate solution design and implementationSupport prompt design, response tuning, and model interaction workflowsOptimize solutions for latency, cost per interaction, and response accuracyEnsure scalability, reliability, and performance of AI solutions in production environmentsParticipate in testing, debugging, and deployment activities across pilot and MVP phasesMonitor system performance and drive continuous improvement of AI capabilitiesAdhere to enterprise standards for security, compliance, and data privacyEducationBachelor's degree in computer science, Engineering, or a related field requiredMaster's degree preferredWork Experience 5+ years of software development experience 2-3 years of hands-on experience in AI/ML or conversational AI developmentExperience in AI agent development and orchestration frameworks preferredExperience integrating with enterprise platforms such as D365, SAP, and contact center systems (e.g., Genesys) Knowledge, Skills, and AbilitiesStrong programming skills in Python, JavaScript, or JavaExperience with AI/LLM frameworks, APIs, and orchestration toolsDeep demonstratable understanding of conversation orchestration, dialog management, and context handlingKnowledge of REST APIs, microservices architecture, and enterprise integrationsFamiliarity with cloud platforms (Azure, AWS, or GCP) Understanding of RAG (Retrieval-Augmented Generation), vector databases, and prompt engineeringAbility to optimize for performance, latency, and cost efficiencyStrong problem-solving and debugging skillsAbility to work in Agile development environmentsEffective communication and collaboration skills across cross-functional teamsPreferred QualificationsExperience with platforms such as Kore.ai, Yellow.ai, Cognigy, or similarExposure to multi-LLM orchestration and model selection strategiesExperience with real-time voice and chat integrations (e.g., Genesys Cloud) Knowledge of DevOps practices, CI/CD pipelines, and monitoring toolsFamiliarity with Responsible AI, security, and compliance frameworks