Python Kubernetes Software Engineer Data Jobs in Clarksville, TX

Job Title:  Sr Software Engineer (AI Platform) 
Locations: Houston, TX; Boston, MA (Hybrid - 2 Days in Office)
Reports to: Manager, Software Engineering 

A quick snapshot... 

As a Senior Software Engineer,you'llbe a key member in a team responsible for the development ofscalable, reliable, and innovative AI/GenAI solutions.You'llcontribute to high-priority projects, ensuring maintainable code and producing high-quality, production-ready applications.You'lloperatewith ahigh degree of technicalexpertise, strategic thinking,effective collaborationacross diverse teams,while helping to mentor and elevate others to meeta very hightechnical bar. 

Why it's a big deal... 

You will be a key contributor to delivering Conga's AI roadmap, ensuring solutions meet high quality standards and timelines. You'll be a core member of the team that will implement complex, large-scale AI systems. You'll also have the opportunity to work cross-functionally to resolve issues, mentor junior members, and help to foster a culture of continuous learning and technical excellence. All of this adds up to an exciting, challenging, and always interesting place to work, where complex problems are found and solved every day. 

Here's what we're looking for... 

Responsibilities: 

Advanced Software Development: Design, develop, and optimize high-quality code for complex software applications and systems, maintaining high standards of performance, scalability, and maintainability. Drive best practices in code quality, documentation, and test coverage. 

GenAI Product Development: 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. 

Technical Leadership: Take ownership of architecture and technical decisions for AI/ML projects. Mentor junior engineers, review code for adherence to best practices, and ensure the team follows a high standard of technical excellence. 

Project Ownership: Lead execution and delivery of features, managing project scope, timelines, and priorities in collaboration with product managers. Proactively identify and mitigate risks to ensure successful, on-time project completion. 

Architectural Design: Contribute to the architectural design and planning of new features, ensuring solutions are scalable, reliable, and maintainable. Engage in technical reviews with peers and stakeholders, promoting a product suite mindset. 

Code Review & Best Practices: Conduct rigorous code reviews to ensure adherence to industry best practices in coding standards, maintainability, and performance optimization. Provide feedback that supports team growth and technical improvement. 

Testing & Quality Assurance: Design and implement robust test suites to ensure code quality and system reliability. Advocate for test automation and the use of CI/CD pipelines to streamline testing processes and maintain service health. 

Service Health & Reliability: Monitor and maintain the health of deployed services, utilizing telemetry and performance indicators to proactively address potential issues. Perform root cause analysis for incidents and drive preventive measures for improved system reliability. 

DevOps Ownership: Take end-to-end responsibility for features and services, working in a DevOps model to deploy and manage software in production. Ensure efficient incident response and maintain a high level of service availability. 

Documentation & Knowledge Sharing: Create and maintain thorough documentation for code, processes, and technical decisions. Contribute to knowledge sharing within the team, enabling continuous learning and improvement. 

Minimum Qualifications: 

Educational Background: Bachelor's degree in Computer Science, Engineering, or a related technical field; Master's degree preferred. 

Experience: 6+ years of professional software development experience, including significant experience with AI/ML or GenAI applications. Demonstrated expertise in building scalable, production-grade software solutions. 

Technical Expertise: Advanced proficiency in Python, FastAPI, PyTest, Celery, and other Python frameworks. Deep knowledge of software design patterns, object-oriented programming, and concurrency. 

Cloud & DevOps Proficiency: Extensive experience with cloud technologies (e.g., GCP, AWS, Azure), containerization (e.g., Docker, Kubernetes), and CI/CD practices. Strong understanding of version control systems (e.g., GitHub) and work tracking tools (e.g., JIRA). 

AI/GenAI Knowledge: Familiarity with GenAI frameworks (e.g., LangChain, LangGraph), MLOps, and AI lifecycle management. Experience with model deployment and monitoring in cloud environments.

Here's what will give you an edge... 

AI & Machine Learning: Hands-on experience with advanced ML algorithms, including generative models, NLP, and transformers. Knowledge of industry-standard AI frameworks (e.g., TensorFlow, PyTorch) and experience with data preprocessing and model evaluation. 

Data & Analytics Tools: Proficiency with relational and NoSQL databases (e.g., MongoDB, MSSQL, PostgreSQL) and analytics platforms (e.g., BigQuery, Snowflake, Tableau). Experience with messaging systems (e.g., Kafka) is a plus. 

Testing & Quality: Experience with test automation tools (e.g., PyTest, xUnit) and CI/CD tooling such as Terraform and GitHub Actions. Strong emphasis on building resilient and testable software. 

Advanced Cloud Knowledge: Proficiency with GCP technologies such as VertexAI, BigQuery, GKE, GCS, and DataFlow, with a focus on deploying AI models at scale. 

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