AI Engineering & Innovation Manager.Customer and Partner Management

Job Purpose

To lead the AI Engineering & Innovation function, with primary focus on AI Development, AI/ML Engineering, Generative AI, and Agentic AI solutions, supported by strong background in platform engineering and full-stack architecture. Responsible for delivering cutting-edge AI solutions, including AI Agents, Agentic Automation, OCR, Chatbots, Conversational AI, Speech-to-Text, Text-to-Speech, Voicebots, and local LLM deployments—while ensuring solutions are scalable, secure, production-ready, and aligned with enterprise architecture standards. The role drives end-to-end innovation, from lean experimentation and proof-of-concepts to enterprise-scale deployment, ensuring AI solutions are aligned with business strategy, customer experience goals, and market-leading practices.

Report To Position Name

Leadership & Strategy Lead and manage a team of AI Development Engineers, AI/ML Engineers, AI Agent Engineers, and AI Support Engineers. Define AI Engineering and Innovation roadmap aligned with corporate digital transformation strategy. Evaluate emerging AI technologies (LLMs, local LLMs, RAG, AI agents, agent frameworks, vector databases, orchestration layers, and autonomous workflows) and introduce new capabilities. Drive adoption of AI to enhance customer care, CVM, digital channels, enterprise services, and internal efficiency. Establish standards for reusable AI components, agent design, governance, and scalable enterprise AI adoption. AI Development Oversee design and development of AI/ML models, Generative AI applications, reusable AI agents, and agentic workflows for OCR, NLP, Chatbots, Conversational AI, and automation use cases. Guide teams in model training, fine-tuning, prompt engineering, evaluation, deployment, and agent orchestration. Lead deployment and optimization of local / on-prem LLM models, including model serving, inference optimization, GPU utilization, and continuous tuning. Drive integration of speech-to-text, text-to-speech, voicebot, and voice persona capabilities into customer-facing and enterprise applications. Ensure compliance with data governance, model governance, ethical AI use, and responsible AI principles. Design modular, reusable, and scalable AI agents with governance controls and shared services. AI Platforms Engineering Provide architectural oversight leveraging strong platform engineering and full-stack development background(Java, Spring Boot, Node.js, Angular). Ensure robust solution architecture using microservices, containerization, Docker, Kubernetes / OpenShift, Amazon EKS orchestration, APIs, and CI/CD pipelines. Lead production deployment and go-live readiness with full focus on security controls, vulnerability management, secure coding practices, and infrastructure hardening. Integrate AI solutions with enterprise platforms, core systems, vector stores, tool layers, and backend services. Oversee performance, scalability, resilience, and production readiness of AI applications and services. Innovation, Proof-of-Concepts & Productization Lead innovation lifecycle: identify opportunities, run lean experiments, build PoCs, validate impact, and scale successful use cases to production. Collaborate with business units to co-create AI-powered products, agentic workflows, and automation services. Drive rapid experimentation cycles with measurable business impact and customer value. Ensure accelerated time-to-value and time-to-market for AI solutions while maintaining quality and security. Operations & AIOps Ensure operational readiness of deployed AI applications through AIOps, MLOps, and LLMOps monitoring and automation. Oversee incident resolution, model monitoring, change management, and continuous improvement. Maintain SLAs and service reliability for critical AI-enabled business applications. Ensure continuous security patching, vulnerability remediation, and model/runtime lifecycle management.

QUALIFICATIONS_ESSENTIAL

Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related field

QUALIFICATIONS_DESIRABLE

Innovation Drive adoption of next-gen AI architectures (Agentic orchestration, vector databases, RAG pipelines). Lead experimentation with new AI platforms and integration models. Skills & Abilities Strong leadership, people management, and cross-functional collaboration. Excellent communication, presentation, and stakeholder engagement skills. Ability to manage multiple parallel projects and deliver under pressure.

EXPERIENCE_ESSENTIAL

8+ years of experience in AI/ML engineering and software development. At least 3–5 years in a leadership/managerial role overseeing AI development teams

EXPERIENCE_DESIRABLE

Strong knowledge of AI/ML technologies (Machine Learning, NLP, Generative AI, Agentic AI, Conversational AI, OCR, autonomous workflows). Proven experience in AI development, reusable agent design, and scalable AI solution engineering. Strong hands-on familiarity with cloud platforms and their AI portfolios, including AWS (Bedrock, SageMaker), Microsoft Azure AI services, and Google Cloud Vertex AI / GenAI services. Solid background in platform engineering, full-stack architecture, microservices, containerization, APIs, and orchestration platforms such as Docker, OpenShift, and EKS. Proven go-live deployment experience with strong focus on security, vulnerability management, and production hardening. Experience in deploying and managing local / on-prem LLM models and inference environments. Familiarity with speech technologies (speech-to-text, text-to-speech, voicebots, voice persona solutions). Deep understanding of cloud, DevOps, MLOps, LLMOps, governance, and observability tools. Strong knowledge of lean experimentation methodologies with impact-driven delivery. Knowledge of telecom, customer care, CVM, sales, and enterprise domains is a plus.

CERTIFICATIONS_ESSENTIAL

N/A