Daily Progress
Software Engineer (Generative AI and Cloud Solutions)
Daily Progress, Mc Lean, Virginia, us, 22107
We are seeking a highly skilled and proactive Software Engineer with hands-on expertise in Java, Python, and Node.js to join our innovative technology team. This role is focused on developing and deploying Generative AI solutions, leveraging Google Cloud Platform (GCP) and Vertex AI to create cutting-edge applications. The ideal candidate will have a deep understanding of cloud architecture, data engineering, and be well-versed in data management using BigQuery, SQL, and NoSQL databases. As a self-starter with strong experience in cloud-native environments, you will play a critical role in designing, implementing, and optimizing scalable, AI-driven applications.
Key Responsibilities: End-to-End Software Development:
Develop, test, and deploy high-quality code in Java, Python, Node.js, and Typescript to build reliable, scalable, and secure applications. Ensure best coding practices, including code reviews, version control, and thorough documentation, are maintained across projects. Create and maintain APIs and backend services that enable seamless data flows and integration with AI models.
Generative AI Development:
Design and deploy Generative AI models using Vertex AI on Google Cloud Platform, building robust AI solutions to solve business problems. Fine-tune and optimize AI models for performance, accuracy, and scalability in production environments. Work with data scientists and ML engineers to incorporate the latest AI techniques and improve model performance over time.
Cloud Architecture and Infrastructure:
Architect cloud-based systems and applications using GCP's full suite of tools, ensuring high performance, scalability, and cost-effectiveness. Knowledge of CI/CD pipelines and automation scripts for seamless deployment, monitoring, and scaling of AI and backend applications.
Data Engineering and Management:
Design and manage data models using BigQuery, SQL, and NoSQL databases, ensuring optimal performance for both transactional and analytical data. Develop and maintain ETL pipelines to support large-scale data ingestion, processing, and transformation from multiple sources. Implement data governance practices, including data quality checks, validation, and monitoring, to ensure accuracy and compliance.
Solution Architecture and Technical Design:
Lead solution design sessions to define project requirements, system specifications, and technical architecture. Collaborate with product and design teams to translate business needs into technical solutions that are scalable, flexible, and aligned with best practices. Create technical documentation for architecture, design patterns, and deployment processes to ensure knowledge sharing and future scalability.
Collaboration and Mentorship:
Work closely with cross-functional teams, including product managers, data scientists, and designers, to drive projects from concept to production. Foster a collaborative team environment that encourages knowledge sharing, continuous improvement, and innovation.
System Performance Monitoring and Optimization:
Monitor application performance, proactively identifying and resolving bottlenecks, latency issues, and potential areas for optimization. Set up monitoring tools and dashboards to track application health, performance, and resource utilization in real-time. Balance performance, cost, and scalability to achieve business objectives.
Continuous Improvement and Agile Practices:
Participate in agile development processes, including sprint planning, stand-ups, and retrospectives to deliver projects on time. Embrace a mindset of continuous learning, staying current with industry trends, emerging technologies, and advancements in Generative AI and cloud solutions. Drive process improvements within the team, including workflow optimizations, automation, and integration of new tools to increase efficiency.
Risk Assessment and Security Implementation:
Conduct risk assessments for software projects, identifying potential issues and implementing solutions to mitigate them. Ensure that all systems are secure, implementing necessary encryption, access controls, and security best practices. Collaborate with the security team to regularly review, test, and improve security protocols.
Innovation and R&D:
Lead research initiatives to explore new technologies, AI frameworks, and GCP tools to continuously push the boundaries of what's possible. Identify opportunities to apply emerging AI technologies to address business challenges and improve customer experience. Conduct experiments and proof-of-concepts (POCs) to validate new approaches and assess feasibility for future projects.
Qualifications: Experience: 5+ years of software engineering experience, with at least 2 years focused on cloud architecture and Generative AI, preferably on GCP. Technical Skills:
Proficient in Java, Python, and Node.js for backend development and AI integration. Experience in frontend development such as ReactJS. Strong expertise in Google Cloud Platform (GCP), especially Vertex AI and related AI tools for Generative AI projects. Proficient in BigQuery, SQL, and NoSQL databases for data modeling and management.
Problem-Solving: Proven ability to troubleshoot, debug, and resolve complex technical challenges independently. Self-Starter: Demonstrated capability to independently initiate, manage, and deliver projects with minimal guidance. Communication Skills: Ability to convey complex technical information effectively and collaborate with cross-functional teams. Preferred Qualifications: Familiarity with agile and DevOps practices for streamlined development and deployment. Knowledge of additional cloud services, microservices, and data pipeline architectures. Experience with machine learning frameworks and libraries is a plus. Experience in Ad tech and Digital Marketing is a plus. The annualized base salary for this role will range between $130,000 and $150,000. Base compensation is reflective of many factors, including, but not limited to, the market in which one lives/works, individual education level, skills, certifications and experience. Note: variable compensation is not reflected in these figures and based on the role, may be applicable.
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Key Responsibilities: End-to-End Software Development:
Develop, test, and deploy high-quality code in Java, Python, Node.js, and Typescript to build reliable, scalable, and secure applications. Ensure best coding practices, including code reviews, version control, and thorough documentation, are maintained across projects. Create and maintain APIs and backend services that enable seamless data flows and integration with AI models.
Generative AI Development:
Design and deploy Generative AI models using Vertex AI on Google Cloud Platform, building robust AI solutions to solve business problems. Fine-tune and optimize AI models for performance, accuracy, and scalability in production environments. Work with data scientists and ML engineers to incorporate the latest AI techniques and improve model performance over time.
Cloud Architecture and Infrastructure:
Architect cloud-based systems and applications using GCP's full suite of tools, ensuring high performance, scalability, and cost-effectiveness. Knowledge of CI/CD pipelines and automation scripts for seamless deployment, monitoring, and scaling of AI and backend applications.
Data Engineering and Management:
Design and manage data models using BigQuery, SQL, and NoSQL databases, ensuring optimal performance for both transactional and analytical data. Develop and maintain ETL pipelines to support large-scale data ingestion, processing, and transformation from multiple sources. Implement data governance practices, including data quality checks, validation, and monitoring, to ensure accuracy and compliance.
Solution Architecture and Technical Design:
Lead solution design sessions to define project requirements, system specifications, and technical architecture. Collaborate with product and design teams to translate business needs into technical solutions that are scalable, flexible, and aligned with best practices. Create technical documentation for architecture, design patterns, and deployment processes to ensure knowledge sharing and future scalability.
Collaboration and Mentorship:
Work closely with cross-functional teams, including product managers, data scientists, and designers, to drive projects from concept to production. Foster a collaborative team environment that encourages knowledge sharing, continuous improvement, and innovation.
System Performance Monitoring and Optimization:
Monitor application performance, proactively identifying and resolving bottlenecks, latency issues, and potential areas for optimization. Set up monitoring tools and dashboards to track application health, performance, and resource utilization in real-time. Balance performance, cost, and scalability to achieve business objectives.
Continuous Improvement and Agile Practices:
Participate in agile development processes, including sprint planning, stand-ups, and retrospectives to deliver projects on time. Embrace a mindset of continuous learning, staying current with industry trends, emerging technologies, and advancements in Generative AI and cloud solutions. Drive process improvements within the team, including workflow optimizations, automation, and integration of new tools to increase efficiency.
Risk Assessment and Security Implementation:
Conduct risk assessments for software projects, identifying potential issues and implementing solutions to mitigate them. Ensure that all systems are secure, implementing necessary encryption, access controls, and security best practices. Collaborate with the security team to regularly review, test, and improve security protocols.
Innovation and R&D:
Lead research initiatives to explore new technologies, AI frameworks, and GCP tools to continuously push the boundaries of what's possible. Identify opportunities to apply emerging AI technologies to address business challenges and improve customer experience. Conduct experiments and proof-of-concepts (POCs) to validate new approaches and assess feasibility for future projects.
Qualifications: Experience: 5+ years of software engineering experience, with at least 2 years focused on cloud architecture and Generative AI, preferably on GCP. Technical Skills:
Proficient in Java, Python, and Node.js for backend development and AI integration. Experience in frontend development such as ReactJS. Strong expertise in Google Cloud Platform (GCP), especially Vertex AI and related AI tools for Generative AI projects. Proficient in BigQuery, SQL, and NoSQL databases for data modeling and management.
Problem-Solving: Proven ability to troubleshoot, debug, and resolve complex technical challenges independently. Self-Starter: Demonstrated capability to independently initiate, manage, and deliver projects with minimal guidance. Communication Skills: Ability to convey complex technical information effectively and collaborate with cross-functional teams. Preferred Qualifications: Familiarity with agile and DevOps practices for streamlined development and deployment. Knowledge of additional cloud services, microservices, and data pipeline architectures. Experience with machine learning frameworks and libraries is a plus. Experience in Ad tech and Digital Marketing is a plus. The annualized base salary for this role will range between $130,000 and $150,000. Base compensation is reflective of many factors, including, but not limited to, the market in which one lives/works, individual education level, skills, certifications and experience. Note: variable compensation is not reflected in these figures and based on the role, may be applicable.
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