8+ or more years of experience in the Software Engineering industry with a record of increasing responsibility leading software development initiatives, and 3+ years managing teams.
Deep understanding of the Software Development Lifecycle (SDLC) and Machine Learning Lifecycle (MLL).
Lead and drive the strategy, vision and roadmap for building robust, scalable AI/ML foundations and platforms — including but not limited to:
- Feature stores
- Distributed ML model training
- Model versioning and evaluation
- Monitoring, drift detection, and automated retraining pipelines
- Responsible AI, model explainability, and fairness assessments
Experience with productionizing ML models and integrating them into real-time and batch applications. Work closely with data science partners and domain engineering teams to understand AI/ML use cases and build corresponding foundations for personalization, NLP, forecasting, recommendations, and generative AI.
Experience using a popular programming language such as: Python (preferred), Java, C#, Scala, etc.
Solid understanding of modern software development practices including object-oriented programming, concurrency, design patterns, microservices architecture, RESTful API design, and test-driven development.
Experience with software testing concepts and tools: white/black box testing, coverage analysis, mocking, PyTest/xUnit, Selenium, etc.
Hands-on experience with GCP technologies such as BigQuery, GKE, GCS, DataFlow, Kubeflow, and Vertex AI — or equivalent services in AWS and/or Azure.
Familiarity with ML frameworks and tools such as TensorFlow, PyTorch, MLflow, scikit-learn, HuggingFace Transformers, etc.
Strong experience with Infrastructure-as-Code and CI/CD tools used to automate deployment to cloud platforms: Terraform, GitHub Actions, Concourse, Ansible, etc.
Excellent leadership, decision-making, and communication skills, with the ability to translate business needs into engineering outcomes.
Experience with AI product lifecycle management, including experimentation tracking, model governance, and release management.
Experience with Python is ideal; Java/Spring is a strong plus.
Education: Bachelor’s degree in computer science, Engineering, or a related technical field; Master’s degree preferred
Are you the person we’re looking for?
Provide engineering leadership and mentorship to a team of software engineers.
Be a strong engineering leader responsible for executing the Conga AI roadmap using agile practice.
Experience implementing scalable data and AI/ML solutions in a product-driven technology environment.
Manage, lead, and motivate cross-functional, interdisciplinary teams of software engineers to achieve strategic and tactical business outcomes.
Mentor and grow engineers in your team, fostering a culture of teamwork, accountability, and continuous improvement.
Demonstrated ability to skillfully hire, coach, and performance manage a team of technology professionals.
Partner with others at Conga to ensure engineering tasks are understood, broken down, and implemented to the highest of quality standards.
Collaborate with members of the team to solve challenging engineering tasks on time and with high quality.
Encourage skill growth of your team members.
Assist and adhere to enforcement of project deadlines and schedules.
Actively communicate with team members to clarify requirements and overcome obstacles to meet the team goals.
Highly technical, confident at the operational management level and comfortable in an engineering-heavy organization.
Track record of being a strong leader, with the ability to influence across teams and levels.
Work with development teams in an agile context as it relates to software development.