Accolite

Lead ML Integration Engineer

Posted On

July 21, 2025

Location

Chennai, Tamil Nadu

Experience Level

6 - 9 Years Exp.

Job Type

Full Time

Apply By

Aug. 16, 2025

Job Description

About Client

Enterprise Analytics (EA) stands at the forefront of 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 to bank’s core value of being enterprising, we are incredibly thrilled about strengthening this strategic unit’s capabilities for the bank, envisioning significant progress and innovation. We firmly believe that advanced analytics is a pivotal factor in delivering premier AI services to our stakeholders.

Your Profile

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

Your Role

This Lead ML / Integration Engineer role focuses on building and integrating Generative AI and Agentic AI solutions into enterprise environments. You will work closely 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 a must-have.
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 used both for ML and automation tasks
Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
Knowledge of Workflow Orchestrator, such as Ctrl-M
Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, OpenTelemetry.

Soft Skills

Excellent communication skills
Attention to detail
Strong problem-solving mindset with a can-do attitude
Strong Organizational skills
Visual Thinking
Empowering delegation
Mentorship and coaching

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