Sr. Associate Software Engineer

We are seeking a highly motivated and skilled Senior Associate Software Engineer to join our AI Platform team. This role is ideal for someone passionate about building scalable, reliable, and high-performance AI infrastructure and services. You will work closely with machine learning engineers, data scientists, and platform architects to design and implement core components of our AI/ML platform, enabling seamless development, deployment, and monitoring of AI models across the enterprise.

You will contribute to the development of reusable platform components, automation of ML workflows, and integration of AI capabilities into production systems. This is a hands-on engineering role requiring strong software development skills, cloud-native architecture experience,

Roles & Responsibilities:

• Design, develop, and maintain core components of the AI/ML platform including model training pipelines, deployment services, and monitoring tools.
• Collaborate with ML engineers and data scientists to understand requirements and translate them into scalable platform features.
• Implement automation for model lifecycle management including versioning, testing, deployment, and rollback.
• Develop reusable libraries and APIs to support AI/ML workflows and integrations.
• Ensure platform reliability, scalability, and performance through rigorous testing and monitoring.
• Support integration of security, compliance, and governance features into the AI platform.
• Participate in sprint planning, provide technical estimates, and contribute to architectural decisions.
• Continuously improve platform capabilities by evaluating and integrating emerging technologies.

Must-Have Skills:

• Strong programming skills in Python, or Java.
• Experience building distributed systems and microservices.
• Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Solid understanding of CI/CD pipelines and DevOps practices.
• Experience with cloud platforms (AWS, GCP, Azure) and cloud-native services.
• Understanding AI/ML lifecycle and model deployment best practices.
• Ability to learn quickly, be organized and detail oriented.

Good-to-Have Skills:

• Experience with big data tools (Spark, Hadoop) and data pipeline development.
• Familiarity with model monitoring and observability tools.
• Knowledge of security principles and compliance in AI systems.
• Experience with infrastructure-as-code tools (Terraform, CloudFormation).
• Exposure to GenAI technologies and frameworks (e.g., LangChain, Vector DBs).

Education and Professional Certifications:

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 5–9 years of experience in software engineering, preferably in AI/ML platform development.
• Certifications in cloud platforms or AI/ML technologies are a plus (e.g., AWS AI, Azure AI Engineer, Google Cloud ML).

Soft Skills:

• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills.
• Ability to work effectively with global, virtual teams.
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.
• Strong presentation and public speaking skills.