As the most trusted global leader in data-first contract lifecycle management (CLM) software, Agiloft helps organizations manage the end-to-end process of proposing, negotiating, signing, and leveraging contracts using our flexible Data-first Agreement Platform (DAP). With contract data as the foundation, customers quickly and collaboratively reach agreement and leverage contract visibility to thrive with competitive advantage. Employing powerful, pragmatic artificial intelligence as a legal force multiplier, and robust integration capabilities as a data liberator, organizations around the world trust Agiloft’s certified implementers to deliver connected, intelligent, and autonomous solutions across the entire contract lifecycle.
Top analysts like Gartner, Forrester, and IDC agree, all showing Agiloft as a leader in the CLM space. Our no code platform is easily managed and administered by business users, which is why Agiloft is the contract you keep: nearly a full 100% of new customers are satisfied with their initial implementations, and some 97% of customers renew every year. Ours is a growing, vibrant, successful company that is at the forefront of a market that is becoming a must-have for all organizations.
We believe that the way to build the strongest, most vibrant place to work is to bring in individuals from all walks of life, and to support them in bringing their authentic selves to their day, every day. Our working philosophy is that “EX = CX”: when employee experience is excellent, so is customer experience. We support multiple Employee Resource Groups (ERGs), and offer a working environment that supports healthy work/life balance, including floating holidays and a quarterly, no-questions-asked wellness day.
Job Responsibilities
Build and maintain software applications in our suite of enterprise software products
Work with product managers and designers to brainstorm bottom-up solutions to novel problems
Collaborate with AI engineers to efficiently utilize commercial large language model (LLM) APIs
Continuously improve the code quality, extensibility, scalability, and test coverage of software projects
Make architecture and cloud-engineering decisions in conjunction with other engineers
Develop and improve infrastructure-as-code stacks, CI/CD pipelines, and monitoring/observability tools
Improve internal developer tools, workflows, and best practices to enhance team efficiency
Provide consistent feedback to management regarding the quality of the team, the state of the tech stack, and relationships with stakeholders
Troubleshoot and resolve complex issues across the entire application stack
Mentor junior team members
Participate in incident response and disaster recovery efforts
Leverage AI-assisted tools to enhance productivity, streamline workflows, and support day-to-day activities
Other duties as assigned
Required Qualifications
Bachelor's degree in Computer Science, Information Technology, or related field (or equivalent experience)
Minimum of 5 years of professional experience as a software engineer
Comfortable working with Python in core application code
Experience building modern, cloud-native applications using serverless technology (API Gateway, Lambda, DynamoDB, or similar)
Interest in building enterprise software with deep customer empathy, taking pride in contributing to a world class end-to-end user experience
Strong problem-solving, collaboration, teamwork and communication skills
Eagerness to learn and adapt to new technologies and tools
Proficiency in using relevant AI Tools in the SLDC (Cursor, GitHub Copilot) coding, and/or API integrations
Deep understanding of:
Version control systems (Git)
Relational databases and data modeling (Postgres preferred)
Infrastructure as Code in AWS (CloudFormation, SAM)
RESTful API design and documentation
CI/CD tools such as GitHub Actions or similar
Containerization and orchestration (Docker, ECS)
Enterprise-scale cloud engineering in AWS
Modern software development lifecycle on an agile product team
Preferred Qualifications
Interest in team leadership and career growth
Experience building applications on top of LLMs using commercial APIs
Familiarity with Postgres, query optimization, and database indexing
Exposure to data science tooling in Python (numpy, scipy, scikit-learn, pandas)
Experience with monitoring and observability across deployments and tenants
Interest in application security and cloud security
