Senior Software Developer

DNV•San Diego, CA

9d•Hybrid

About The Position

The Senior Software Developer designs, develops, and maintains data services, APIs, backend systems, and AI-ready data foundations that support scalable platform capabilities across Digital & Transformation. Working in the Data & AI Engineering section, the role provides hands-on engineering expertise in Python, SQL, FastAPI, data modeling, API development, and cloud-native platform technologies. It supports deterministic domain workflows through robust backend services and AI-enabled capabilities through clean, structured, searchable, and governed data foundations. The role works closely with Product, AI Engineering, Application Engineering, Solution Engineering, Platform Reliability, Architecture, and Security teams to turn complex business and domain requirements into reliable, performant, secure, and maintainable software. The position is based in the San Diego, California office, with a hybrid schedule typically involving three days per week at a DNV office or client location/site. Other DNV offices may also be considered; role-specific details will be shared during the interview process.

Requirements

Bachelor's or master's degree in computer science, Software Engineering, Information Systems, Engineering, or a related field, or equivalent practical experience.
At least 5 years of experience developing production software applications, APIs, backend services, platform capabilities, or data-driven solutions.
Strong hands-on experience with Python, SQL, and API development frameworks such as FastAPI.
Experience designing and implementing scalable, maintainable, and secure software systems.
Experience working in Agile, Scrum, DevOps, or similar software delivery environments.
Experience using Azure DevOps, Jira, or comparable development and delivery tools.
Strong understanding of software architecture, API design, data modeling, automated testing, observability, performance optimization, and production support.
Experience building services or APIs supporting application workflows, analytics solutions, AI-enabled capabilities, or enterprise platforms.
Experience with CI/CD, source control, code review, monitoring, logging, and secure development practices.
Experience with Azure, AWS, or comparable cloud platforms; Azure experience is preferred.
Ability to translate complex business and domain requirements into practical software solutions.
Strong collaboration, problem-solving, communication, and organizational skills.
Ability to work effectively in globally distributed and multidisciplinary teams.
Strong written and verbal English communication skills.
Must undergo pre-employment drug and background screening.

Nice To Haves

Background in energy, renewables, infrastructure, assurance, certification, or other technically complex industries.
Experience in product-led, platform-based, or software-as-a-service environments.
Experience deploying agents securely and efficiently.
Experience developing backend services, platform APIs, or shared engineering capabilities.
Familiarity with low-code or hybrid development environments.
Experience integrating software across multiple systems or enterprise platforms.
Experience supporting AI-enabled applications, retrieval-based systems, document processing workflows, or machine-learning-adjacent solutions.
Familiarity with vector databases, data governance, observability, lineage, or AI data preparation workflows.
Experience with Azure cloud services, Azure DevOps, cloud security patterns, identity management, and enterprise platform security.
Experience contributing to reusable software standards, API guidelines, architectural patterns, or shared engineering practices.

Responsibilities

Design, develop, test, and maintain APIs and platform capabilities that support Product and Engineering objectives.
Contribute to solution design, implementation, code review, testing, documentation, and production support.
Translate business requirements and domain expertise into scalable, maintainable, production-ready software.
Follow and contribute to engineering standards for API design, data modeling, testing, observability, documentation, and maintainability.
Develop reusable services and components for consistent implementation across platform capabilities.
Collaborate with cross-functional teams to deliver secure, high-quality, reliable software solutions.
Support software solutions for applications, workflows, analytics, reporting, and AI-enabled capabilities.
Design and build Python-based services and FastAPI endpoints that expose platform capabilities and domain-specific functionality.
Develop SQL solutions for storing, querying, transforming, validating, and serving business data.
Collaborate with Application Engineering on API contracts, integration patterns, performance, and interoperability.
Implement secure, scalable, maintainable APIs for internal and customer-facing applications.
Contribute to integrations connecting applications, data services, AI-enabled capabilities, and enterprise platforms.
Support adoption of reusable platform services, shared capabilities, and standardized integration patterns.
Prepare, structure, validate, store, retrieve, and govern data for AI-enabled workflows, analytics, search, and customer-facing applications.
Contribute to data preparation approaches such as metadata enrichment, retrieval optimization, evaluation datasets, and quality feedback mechanisms.
Partner with AI Engineering on retrieval-augmented workflows, document processing pipelines, evaluation, and AI solution development.
Develop and maintain secure, traceable, maintainable AI-ready data assets for downstream use.
Support deterministic business logic through APIs, reference data, calculations, and reusable services where traditional software approaches are appropriate.
Develop observable, scalable, secure, performant, production-ready software.
Contribute to CI/CD pipelines, automated testing, deployment automation, monitoring, logging, and operational support.
Follow secure software development practices aligned with organizational security requirements and industry standards.
Implement controls for data protection, access management, auditability, validation, and operational resilience.
Work with Platform Reliability and Security teams to ensure services and data assets are governed, documented, and maintainable.
Troubleshoot issues, tune performance, conduct root cause analysis, and resolve production issues.
Use AI-assisted development tools to improve coding, testing, documentation, troubleshooting, and engineering productivity.
Apply modern development practices that balance speed, quality, maintainability, and security, and contribute to responsible use of AI-assisted workflows.
Contribute to continuous improvement initiatives and share engineering knowledge, reusable patterns, and best practices through collaboration and code reviews.
Participate in agile activities, including sprint planning, backlog refinement, estimation, reviews, and retrospectives.
Communicate technical concepts, implementation approaches, and trade-offs to technical and non-technical stakeholders.
Contribute to technical documentation, implementation guidance, and knowledge sharing across engineering teams.

Benefits

Paid time off, including vacation, sick days, company holidays, and personal days.
Multiple medical and dental benefit plans.
Vision benefits.
Spending accounts, including FSA, Dependent Care, and Commuter Benefits, and a company-seeded HSA.
Employer-paid, therapist-led virtual care services through Talkspace.
401(k) with company match.
Company-provided life insurance and short-term and long-term disability benefits.
Education reimbursement program.
Flexible work schedule with hybrid opportunities.
Charitable Matched Giving and Volunteer Rewards through the Impact Program.
Company-paid volunteer time off (VTO).
Career advancement opportunities.