Role: Senior Software Engineer
Reports to: Sr. Manager, Software Engineering
Location: Houston, TX; Boston, MA;
A quick snapshot...
As a Senior Software Engineer at Conga, you will be a key contributor to the design, development, and deployment of advanced AI and generative AI-based products. You will drive technical innovation, lead complex projects, and collaborate closely with cross-functional teams to deliver high-quality, scalable, and maintainable solutions. This role requires a strong background in software development, AI/ML techniques, and DevOps practices, along with the ability to mentor junior engineers and contribute to strategic technical decisions.
Why it's a big deal...
As a Senior Software Engineer, you will play a critical role in shaping the future of Conga's AI-powered product portfolio. You'll lead the development of scalable, production-grade solutions that bring generative AI capabilities to life, while influencing architecture, engineering best practices, and delivery execution. Your work will directly impact product innovation, platform reliability, and the ability of our teams to build intelligent, high-performing solutions at scale.
Are you the person we're looking for?
Related experience.
At least 6 years of professional software development experience, including significant experience building AI/ML or generative AI applications. Demonstrated success developing scalable, production-grade software solutions and leading complex technical initiatives from design through deployment.
Technical Expertise:
- Advanced proficiency in Python, FastAPI, PyTest, Celery, and other Python frameworks
- Deep understanding of software design patterns, object-oriented programming, and concurrency
- Strong experience with cloud technologies such as GCP, AWS, or Azure
- Experience with containerization and orchestration tools such as Docker and Kubernetes
- Familiarity with CI/CD practices, version control systems such as GitHub, and work tracking tools such as JIRA
- Knowledge of generative AI frameworks such as LangChain and LangGraph, along with MLOps and AI lifecycle management
- Experience deploying and monitoring AI models in cloud environments
- Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's degree preferred
Education: A bachelor's degree in Computer Science, Engineering or equivalent
Here's what will give you an edge... - Hands-on experience with advanced machine learning algorithms, including generative models, NLP, and transformers
- Knowledge of industry-standard AI frameworks such as TensorFlow and PyTorch
- Experience with data preprocessing, model evaluation, and AI model optimization
- Proficiency with relational and NoSQL databases such as MongoDB, MSSQL, and PostgreSQL
- Experience with analytics platforms such as BigQuery, Snowflake, or Tableau
- Familiarity with messaging systems such as Kafka
- Experience with test automation tools and CI/CD tooling, including Terraform and GitHub Actions
- Advanced knowledge of GCP technologies such as Vertex AI, BigQuery, GKE, GCS, and Dataflow, particularly for deploying AI models at scale
Responsibilities:- Design, develop, and optimize high-quality code for complex software applications and systems, maintaining high standards of performance, scalability, and maintainability
- Lead end-to-end development of generative AI solutions, from data collection and model training to deployment and optimization
- Experiment with cutting-edge generative AI techniques to enhance product capabilities and performance
- Take ownership of architecture and technical decisions for AI/ML projects
- Mentor junior engineers, review code for adherence to best practices, and promote technical excellence across the team
- Lead execution and delivery of features, managing project scope, timelines, and priorities in collaboration with product managers
- Proactively identify and mitigate risks to support successful, on-time delivery
- Contribute to architectural design and planning for new features, ensuring solutions are scalable, reliable, and maintainable
- Conduct rigorous code reviews and provide actionable feedback that supports team growth and software quality
- Design and implement robust test suites to ensure code quality and system reliability
- Advocate for test automation and CI/CD pipelines to streamline testing and maintain service health
- Monitor and maintain the health of deployed services using telemetry and performance indicators
- Perform root cause analysis for incidents and drive preventive measures to improve system reliability
- Operate in a DevOps model, taking end-to-end ownership of features and services in production
- Create and maintain thorough documentation for code, processes, and technical decisions
- Contribute to knowledge sharing and continuous improvement across the engineering organization
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