As a Lead Software Engineer, you will be at the forefront of designing and developing innovative AI-powered solutions and driving large-scale projects in Python back-end development. You will architect complex systems, lead a team of engineers, and ensure smooth integration of AI and machine learning models into back-end infrastructures. We are seeking a highly skilled Lead Software Engineer to drive the architecture and proof of concepts (POCs). In this role, you will mentor a team of engineers and act as the technical subject matter expert, solving complex programming and design challenges.

Key Responsibilities

• Lead the architecture, design, and development of back-end systems using Python, with a focus on integrating AI and machine learning models into scalable applications.

• Collaborate closely with data scientists to deploy, optimize, and scale AI/ML models, ensuring their seamless functionality in production environments.

• Lead efforts to containerize AI-driven applications using Docker and Kubernetes, managing both development and production environments.

• Use Terraform and Helm to manage cloud infrastructure, automating deployment processes and ensuring scalability on platforms like GCP and AWS.

• Oversee database interactions, optimize performance, and ensure data integrity across SQL and NoSQL databases (PostgreSQL, MongoDB).

• Set up monitoring (using Prometheus, Grafana) and logging frameworks (Loki, ELK stack) to ensure the reliability and security of deployed AI models and applications.

• Participate in client-facing consulting projects, providing technical leadership and expertise in developing AI-powered SaaS solutions.

• Participation in our consulting assignments with our clients

• Development of our Software-as-a-Service products from Heka.ai

• Support to Data Scientists, Data Engineers, and DevOps Engineers in projects with a strong Data component:

• Back-end software development in Python: development of microservices and tools executed on the server (interaction with a database, REST API server, authentication, etc.)

• Deploy and manage containerized applications using Docker and Kubernetes.

• Continuous integration: management of continuous software integration (tests writing, artifacts building, etc.)

• Contribution to the back end, front-end and software architecture of applications