Lead ML Integration Engineer

6 to 9 years of experience
Skills: Python, OpenShift, Kubernetes, LLM Prompt Engineering, RAG, Microservices Architecture

About Client

Enterprise Analytics (EA) stands at the forefront of the bank's vision, aiming to establish the bank as a leader in deploying cutting-edge Machine Learning models. Comprising a team of experts, we focus on enhancing the bank's capabilities in supporting key areas such as Risk, Wealth, Retail, etc., with a strong emphasis on coordination in data management, technology, and internal stakeholder collaboration.

Upholding the bank's core value of being enterprising, we are excited to strengthen this strategic unit's capabilities, envisioning significant progress and innovation. We believe advanced analytics is pivotal in delivering premier AI services to stakeholders.

Your Profile

We seek individuals with highly developed conceptual, strategic, and analytical skills, capable of balancing visionary thinking with practical solutions. The ability to understand, inspire, and mobilize others is crucial. A business-oriented mindset and effective storytelling will drive your success. We are looking for self-starters ready to take on responsibilities enthusiastically.

Your Role

This Lead ML / Integration Engineer role focuses on building and integrating Generative AI and Agentic AI solutions into enterprise environments. You will collaborate with data scientists, architects, and DevOps teams to design, implement, and optimize AI pipelines and infrastructure.

Key Responsibilities:

• Design and implement scalable ML pipelines for Generative and Agentic AI applications.
• Integrate AI models into production environments using containerized platforms such as OpenShift and Kubernetes.
• Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.
• Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.
• Ensure seamless deployment and integration of AI services in cloud environments (e.g., AWS, Azure, GCP).
• Implement and maintain network security protocols to safeguard AI systems and data pipelines.
• Monitor and optimize system performance, reliability, and scalability.
• Support CI/CD processes and infrastructure for AI model deployment and updates.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 7+ years of experience in Machine Learning engineering or AI system integration.
• Hands-on experience with OpenShift, Docker, Kubernetes.
• Knowledge of cloud platforms (e.g., AWS, GCP) is essential.
• Exposure to data and network security and compliance in AI systems.
• Understanding of Generative AI and Agentic AI concepts.
• Experience with LLM prompt engineering or RAG pipelines.
• Knowledge of API integration and microservices architecture.
• Proficiency in Python for ML and automation.
• Good knowledge of Bash and Unix/Linux command-line tools.
• Knowledge of Workflow Orchestrator, such as Ctrl-M.
• Experience with Logging and Monitoring tools like Splunk and Geneos.
• Experience with Observability frameworks like Langfuse, Elastic Stack, Grafana, OpenTelemetry.

Soft Skills

• Strong problem-solving mindset with a can-do attitude.
• Strong organizational skills.
• Visual thinking.
• Mentorship and coaching abilities.

At Bounteous, we value honesty about capabilities and boundaries. We support our team through personal and professional challenges, fostering a supportive environment. Be open about your boundaries and needs; we will always support you.

Christopher Sands

Team Coordinator

Join our fast-growing company to enjoy competitive benefits and career development opportunities. Maintain work-life balance with our health & wellness perks, collaborative culture, and flexible working options.

We foster a diverse environment that fuels creativity, collaboration, and belonging.

We offer development opportunities, mentoring, and support for ongoing learning.

Transform experiences and improve outcomes for global brands.

Work from home, office, or hybrid, coordinating across time zones.

Participate in our corporate social responsibility programs to make a difference.