AI Technical Manager

Job Information

Department Name

Banking

Date Opened

07/02/2026

Industry

IT Services

Job Type

Full time

Work Experience

12 - 15 Years

Required Skills

machine learning

artificial intelligence

+16

City

Chennai

State/Province

Tamil Nadu

Country

India

Zip/Postal Code

600032

About Us

Kumaran Systems: Engineering Future-Ready Transformations Since 1992, Kumaran Systems has been helping enterprises bridge the past and the future, reimagining legacy systems and embracing AI-led possibilities. With over 34 years of delivery excellence, we specialise in re-engineering core applications, driving cloud transformation, and building automation-first, GenAI-enabled ecosystems across the Banking and Financial Services, Insurance, Telecom, and Automotive sectors. We help organisations not just upgrade their systems but reimagine what’s possible.

Why Kumaran?

We blend engineering discipline with AI innovation, helping clients modernise with confidence, automate with clarity, and scale with purpose. Our global delivery model ensures agility, responsiveness, and seamless collaboration, with clients always at the heart of every engagement. At Kumaran, we don’t just solve problems, we engineer future-ready transformations.

Job Description

Job Summary

We are seeking an experienced and results-driven AI Technical Manager to lead the design, development, and delivery of enterprise-grade Artificial Intelligence and Machine Learning solutions. The ideal candidate will have over 10 years of experience in software engineering, data science, or AI/ML, with proven expertise in managing cross-functional teams, defining AI strategy, and delivering scalable AI products. This role requires strong technical leadership, stakeholder management, and the ability to bridge business objectives with AI-driven innovation.

Key Responsibilities

Lead and mentor AI/ML engineering teams to deliver high-quality AI solutions.

Define and execute the AI technology roadmap aligned with business goals.

Design, develop, and deploy scalable AI/ML models and Generative AI applications.

Oversee end-to-end AI solution lifecycle, including data collection, model development, validation, deployment, monitoring, and optimization.

Collaborate with Product Managers, Architects, Engineering teams, and business stakeholders to identify AI use cases and translate business requirements into technical solutions.

Drive adoption of modern AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, NLP, Computer Vision, and Predictive Analytics where applicable.

Establish AI engineering best practices, coding standards, MLOps pipelines, model governance, and responsible AI principles.

Lead architecture reviews and ensure scalability, security, performance, and compliance of AI platforms.

Manage project planning, resource allocation, risk management, and delivery timelines.

Evaluate emerging AI technologies and recommend innovative solutions to improve business outcomes.

Work closely with Data Engineering teams to build robust data pipelines supporting AI initiatives.

Present technical strategies, project updates, and AI adoption plans to senior leadership and executive stakeholders.

Ensure AI solutions comply with organizational security, privacy, and regulatory requirements.

Foster a culture of innovation, continuous learning, and technical excellence.

Required Qualifications

Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.

Master's degree is preferred.

10+ years of experience in Software Engineering, AI/ML Engineering, or Data Science.

Minimum 3–5 years of experience managing technical or AI engineering teams.

Strong hands-on experience in Python and AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, and LangChain.

Experience with Generative AI, Large Language Models (LLMs), prompt engineering, AI Agents, and Retrieval-Augmented Generation (RAG).

Strong understanding of Machine Learning, Deep Learning, NLP, Computer Vision, and recommendation systems.

Experience deploying AI solutions on cloud platforms such as AWS, Azure, or Google Cloud Platform.

Hands-on experience with MLOps tools including MLflow, Kubeflow, Docker, Kubernetes, and CI/CD pipelines.

Experience with vector databases and AI search technologies such as Pinecone, Weaviate, Chroma, or FAISS.

Strong knowledge of SQL, NoSQL databases, and distributed data processing frameworks.

Experience integrating AI models with enterprise applications using REST APIs and microservices.

Strong understanding of software architecture, system design, and scalable distributed systems.

Excellent analytical, problem-solving, communication, and stakeholder management skills.

Preferred Skills

Experience with Agentic AI frameworks and multi-agent systems.

Knowledge of Responsible AI, AI governance, model explainability, and AI ethics.

Experience with Azure OpenAI, OpenAI APIs, Anthropic, Google Gemini, or similar AI platforms.

Familiarity with data engineering tools such as Apache Spark, Kafka, Airflow, or Databricks.

Experience in Agile, Scrum, and DevOps environments.

Relevant certifications in AI, Cloud, or Machine Learning are highly desirable.

Leadership Competencies

Technical Leadership

Strategic Planning

Team Building and Mentoring

Cross-functional Collaboration