Senior AI Engineer

Location: District 3

Salary: upto 2200$ gross

Overview

• Be part of a transformative journey to embed generative AI into the core of banking operations. We&aposre looking for a visionary engineer to lead strategy, architecture, and solutioning for GenAI initiatives that drive real business impact.

Key Responsibilities

• Strategic Leadership & Innovation

- Craft and evolve the banks GenAI strategy, ensuring alignment with business goals and the broader tech roadmap.

- Assess risks, benefits, and ethical considerations of GenAI adoption.

- Develop and maintain a GenAI implementation roadmap with clear milestones and resource planning.

- Collaborate with senior leadership to secure funding and executive sponsorship.

- Stay ahead of the curve by tracking emerging trends, tools, and regulations in GenAI.

• Solution Engineering

- Lead the design and delivery of GenAI solutions tailored to specific business challenges.

- Work closely with data scientists and domain experts to frame problem statements and solution approaches.

- Apply techniques such as natural language processing, image generation, and recommendation systems.

- Evaluate solution performance and iterate to optimize accuracy, efficiency, and business impact.

- Integrate GenAI models into production systems with monitoring and feedback loops.

• Model Development & Deployment

- Build and deploy high-quality generative models (e.g., GPT, BERT, GANs) for NLP, vision, and multi-modal tasks.

- Ensure models are reliable, scalable, and continuously improving.

- Collaborate with IT and operations teams for seamless integration into existing systems.

- Implement data governance and privacy policies to protect sensitive customer data.

Qualifications

• Education

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

• Technical Expertise

- Proficiency in Python (mandatory), R, Julia and Rust.

- Hands-on experience with deep learning frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras.

- Strong foundation in LLMs, NLP, computer vision, and agentic design.

- Familiarity with LLM frameworks: LangChain, LangGraph, LlamaIndex.

- Experience with vector databases: Pinecone, Weaviate.

- Knowledge of prompt engineering and agent orchestration.

- Experience with MLOps tools and practices: CI/CD, Docker, Kubernetes, model versioning.

- Solid understanding of data architecture, governance, and AI lifecycle management.

- Proficiency with productivity tools: Excel, Word, PowerPoint.

• Soft Skills

- Proven ability to lead AI/ML projects from ideation to deployment.

- Strong communication and stakeholder engagement skills.

- Experience working in agile, cross-functional teams.

- Analytical mindset with a passion for innovation and continuous learning.

- Ability to bridge technical and business perspectives effectively.