Description :

IBSFINtech, Indias fastest growing Treasury & FinTech platform provider, is seeking a highly skilled and passionate AI/ML Subject Matter Expert (SME) to drive artificial intelligence adoption and innovation across the organization.

We are a tech product company looking to leverage AI to drive innovation and efficiency in our products and processes. We're seeking an experienced AI Senior Manager to lead the implementation of AI initiatives and upskill our engineering team.

Role Overview :

In this critical role, you will serve as the fulcrum for Artificial Intelligence and Machine Learning in the various products we offer , and will be responsible for building intelligent solutions while guiding employees and business teams in effectively adopting AI/ML technologies. The ideal candidate brings strong hands-on expertise, a mentoring mindset, and the ability to translate advanced AI concepts into practical business applications.

You will work closely with engineering, product, and business stakeholders to embed AI/ML into core processes and foster a data-driven, AI-enabled culture.

Key Responsibilities :

AI/ML Solution Development :

- Identify opportunities for AI adoption in our products and processes

- Design and implement AI-powered features and solutions

- Train and mentor engineers to use AI tools and technologies

- Collaborate with cross-functional teams to integrate AI solutions

- Stay up to date with latest AI trends and technologies

- Drive experimentation and innovation in AI

AI/ML Enablement & Adoption :

- Guide and mentor employees on adopting AI/ML tools, platforms, and methodologies.

- Conduct internal training programs, workshops, and technical demos.

- Develop documentation, playbooks, and reusable frameworks for AI/ML use cases.

- Act as an internal consultant to business and technical teams for AI-driven initiatives.

- Promote organization-wide awareness and adoption of AI/ML capabilities.

Technical Leadership & Mentorship :

- Serve as the primary technical mentor for junior and mid-level AI/ML professionals.

- Review and validate AI/ML solutions developed by internal teams.

- Provide guidance on model selection, feature engineering, and experimentation strategies.

Stakeholder Collaboration :

- Partner with product managers, business leaders, and engineering teams to translate business requirements into AI-driven solutions.

- Present technical concepts and outcomes to non-technical stakeholders.

- Support pre-sales, proposals, and client discussions related to AI/ML (if required).

Required Qualifications :

Experience :

- Proven track record of implementing AI solutions in a product or tech company with 4 to 5 years of hands on experience

- Strong expertise in AI/ML technologies

- Experience with AI-assisted coding tools

- Excellent communication and leadership skills

- Bachelor's or Master's degree in Computer Science or related field

Technical Expertise :

- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).

- Experience in areas such as NLP, Computer Vision, Predictive Analytics, or Generative AI.

- Solid understanding of supervised and unsupervised learning, neural networks, and model optimization.

- Experience with data processing tools (Pandas, NumPy, SQL).

- Knowledge of MLOps, model deployment, and monitoring pipelines.

- Familiarity with cloud platforms (AWS, Azure, or GCP).

Leadership & Communication :

- Demonstrated ability to mentor, train, and enable teams.

- Strong communication skills to explain complex AI concepts clearly.

- Ability to work cross-functionally with business and technical stakeholders.

Education :

- Bachelors or Masters degree in Computer Science, AI, Data Science, Engineering, or a related field.

Preferred Qualifications :

- Experience in enterprise-wide AI transformation initiatives or AI Centres of Excellence.

- Experience with financial data, compliance, or risk modelling.

- Hands-on experience with Large Language Models (LLMs) and prompt engineering.

- Exposure to big data platforms (Spark, Hadoop).

- Experience with containerization tools such as Docker and Kubernetes.

- Relevant AI/ML or Cloud certifications.

Success metrics (non exhaustive) :

- Number of engineers trained on AI/ML tools

- Internal AI workshops / training sessions conducted

- Internal AI adoption rate across teams

- Improvement in AI capability of engineers

- Customer satisfaction improvement for AI features