Senior Software Developer - Generative AI

Senior Software Developer

• Generative AI Procom
• 3.4 Richmond, CA Job Details Contract $75
• $100 an hour 16 hours ago Qualifications AI models Software engineering Continuous Delivery (CD) implementation Tooling .

NET Core C# Software implementation Generative models Git Research AI platforms (beyond public GPTs) Computational framework Machine learning cloud services Machine intelligence Bachelor's degree Model deployment Developing large-scale AI models Cloud solution delivery Developing automated testing protocols Agile software development DevOps automation Machine learning libraries Machine learning frameworks Python Generative AI Providing code feedback Full Job Description Senior Software Developer

• Generative AI Our client is seeking a Intermediate to Senior Generative AI Developer with a strong foundation in working with large language models (LLMs) and a keen interest in building intelligent, agentic systems.

As part of the Innovation Team you'll be working with a cross-functional team to explore, prototype, and implement artificial intelligence technologies to solve complex business problems. This is a hands-on role focused on rapid prototyping, integration, and advancing the practical use of generative AI across business processes. We recognize that agentic AI is an emerging domain. If direct project experience is not available, we encourage applications from candidates with the most applicable mix of skills, curiosity, and relevant experience in LLMs, AI architecture, and software development.

Specific Responsibilities and Deliverables:

Design and build applications using OpenAI, Azure OpenAI, and open-source LLMs Develop and optimize Retrieval-Augmented Generation (RAG) pipelines Explore and implement foundational patterns for multi-agent AI systems using tools like AutoGen, LangChain, or Semantic Kernel Integrate LLMs into enterprise workflows and digital products Use vector databases such as Qdrant, pgvector, and Cosmos DB Leverage Azure AI services and models to enhance capabilities and performance Collaborate with product teams and data scientists to test, refine, and deliver AI use cases Develop prompt strategies, memory handling, and task chaining Maintain clear documentation of models, architecture, and decision-making Stay current with research and best practices in generative and agentic AI Collaborate with cross-functional teams to transition validated concepts to production Participate in Agile ceremonies, code reviews, and DevOps practices Maintain technical documentation and participate in system architecture decisions Provide mentorship to junior developers and support knowledge sharing Establish and evolve AI-native Software Development Lifecycle practices, including integrating AI tools into development workflows (code generation, testing, documentation, debugging, and review) to improve delivery speed, quality, and developer productivity Prototype and operationalize AI-driven development workflows, evaluating emerging tools and approaches for AI-native software engineering and integrating them into the team's SDLC where appropriate

Deliverables:

Prototypes and fully developed, production-grade applications that demonstrate generative and agentic AI capabilities Integration of LLM-based solutions into existing enterprise environments Documentation of models, prompts, workflows, and architectures Regular stakeholder updates and demo presentations Contributions to reusable components and AI development patterns AI-Native Software Development Lifecycle (AI-SDLC): Design, implementation, and continuous improvement of an AI-native Software Development Lifecycle (AI-SDLC), defining standards, guardrails, and best practices for building AI-enabled solutions Integration of AI tools into day-to-day development workflows (e.g., code generation, testing, documentation, debugging, and review) to measurably improve delivery speed, quality, and developer productivity Establishment of AI-assisted quality and reliability practices, including automated test generation, AI-supported validation, and model-aware review processes Development of reference architectures, pipelines, and templates for AI-enabled delivery (e.g., prompt management, evaluation, CI/CD with AI checks) Measurement and reporting of AI-SDLC effectiveness, such as productivity gains, defect reduction, cycle-time improvements, and developer adoption Enablement of teams through guidance, examples, and coaching to drive consistent adoption of AI-native engineering practices across initiative

Mandatory Requirements:

Bachelor's degree in Computer Science or a related STEM field 5-7 years of software development experience, including recent work with LLMs or AI integration Proficiency in Python and experience with AI/ML frameworks (e.g., OpenAI SDKs, LangChain, Hugging Face) Experience in C#, .NET Core, and object-oriented design Interest and understanding of agent-based design concepts and tools (AutoGen, Semantic Kernel, etc.) Familiarity with RAG, GraphRAG, embeddings, and vector databases such as Cosmos DB, pgvector, or Qdrant Experience deploying solutions to the cloud (Azure preferred) Knowledge of APIs, CI/CD pipelines, Git, and Agile software development practices Ability to synthesize complexity and communicate AI capabilities clearly to diverse audiences Experience designing or implementing AI-enabled Software Development Lifecycle (AI-SDLC) practices, including developer copilots, automated test generation, AI-assisted code review, and intelligent documentation workflows Senior Software Developer

• generative AI Assignment Length 12 months Senior Software Developer
• Generative AI Assignment Location Richmond, BC
• 3 days in office