What are the responsibilities and job description for the GenAI Developer position at Inherent Technologies?
Position: GenAI Developer
Location: Nashville, TN***Day 1 Onsite***
Duration: 1 Year
Job Description
Lead the design, development, and implementation of scalable, enterprise-grade Generative AI solutions on the Google Cloud Platform, with a strong focus on the Vertex AI suite.
Architect and build sophisticated Retrieval-Augmented Generation (RAG) systems to ground large language models in HCA's proprietary and domain-specific data, ensuring response accuracy and relevance
Design and implement efficient data pipelines for preparing, processing, and embedding data for use in Vector Stores like Vertex AI Vector Search
Develop and apply innovative data grounding strategies and design the necessary data structures to connect LLMs with real-world, real-time information sources
Spearhead the exploration and implementation of Agentic AI concepts to create autonomous systems capable of complex reasoning and task execution.
Champion and integrate the Model Context Protocol to standardize communication between LLMs and external tools, enhancing system capabilities and interoperability.
Promote a collaborative team environment and work closely with colleagues to achieve business objectives.
Collaborate with stakeholders (e.g., business stakeholders, product owners, project managers, and end users) to understand functional and non-functional requirements for AI systems.
Lead investigations and solution proposals for complex development and design problems in the AI domain.
Guide team members in the scope of work estimation and forecasting for AI-related projects.
Perform proof-of-concept and proof-of-technology tasks to secure buy-in from cohorts and stakeholders for new AI initiatives.
Collaborate with team members to successfully execute development initiatives using Agile practices and principles.
Perform other duties as assigned
Practice and adhere to the "Code of Conduct" philosophy and "Mission and Value Statement."
Education & Experience
Bachelor's degree Computer Science or related field required
8 years of experience a Software development or engineering roles required
Demonstrable experience in delivering Generative AI applications to production in a customer-facing or enterprise environment required
Knowledge, Skills, Abilities, Behaviors Required
Growth mindset and a willingness to learn new skills, technologies, and frameworks in the rapidly evolving field of AI
Advanced knowledge and hands-on experience with GCP Vertex AI, including its generative AI models (e.g., Gemini) and Vertex AI Studio
Deep understanding and practical experience in designing and building Retrieval-Augmented Generation (RAG) architectures
Experience with DevOps tooling (e.g., GitHub, Azure DevOps) and CI/CD for machine learning (MLOps)
Experience with diagramming tools (e.g. Visio)
Strong Experience in cloud native, deploying within cloud environments, serverless development and/or container-based solutions
Knowledge of the Model Context Protocol and its application in enabling LLMs to interact with external tools and data preferred
Familiarity with Agentic AI concepts and frameworks (e.g., LangChain) for building autonomous and multi-agent systems preferred
Experience interfacing with or working within CRM, ERP, eCommerce, or EMR/EHR solutions and common integration patterns
Strong Understanding of agile methodology and software development lifecycles preferred
Ability to sit for long periods of time
Mandatory Skills
Production GenAI experience
Vertex AI / Gemini expertise
hands-on RAG architecture
vector/embedding pipelines
Location: Nashville, TN***Day 1 Onsite***
Duration: 1 Year
Job Description
Lead the design, development, and implementation of scalable, enterprise-grade Generative AI solutions on the Google Cloud Platform, with a strong focus on the Vertex AI suite.
Architect and build sophisticated Retrieval-Augmented Generation (RAG) systems to ground large language models in HCA's proprietary and domain-specific data, ensuring response accuracy and relevance
Design and implement efficient data pipelines for preparing, processing, and embedding data for use in Vector Stores like Vertex AI Vector Search
Develop and apply innovative data grounding strategies and design the necessary data structures to connect LLMs with real-world, real-time information sources
Spearhead the exploration and implementation of Agentic AI concepts to create autonomous systems capable of complex reasoning and task execution.
Champion and integrate the Model Context Protocol to standardize communication between LLMs and external tools, enhancing system capabilities and interoperability.
Promote a collaborative team environment and work closely with colleagues to achieve business objectives.
Collaborate with stakeholders (e.g., business stakeholders, product owners, project managers, and end users) to understand functional and non-functional requirements for AI systems.
Lead investigations and solution proposals for complex development and design problems in the AI domain.
Guide team members in the scope of work estimation and forecasting for AI-related projects.
Perform proof-of-concept and proof-of-technology tasks to secure buy-in from cohorts and stakeholders for new AI initiatives.
Collaborate with team members to successfully execute development initiatives using Agile practices and principles.
Perform other duties as assigned
Practice and adhere to the "Code of Conduct" philosophy and "Mission and Value Statement."
Education & Experience
Bachelor's degree Computer Science or related field required
8 years of experience a Software development or engineering roles required
Demonstrable experience in delivering Generative AI applications to production in a customer-facing or enterprise environment required
Knowledge, Skills, Abilities, Behaviors Required
Growth mindset and a willingness to learn new skills, technologies, and frameworks in the rapidly evolving field of AI
Advanced knowledge and hands-on experience with GCP Vertex AI, including its generative AI models (e.g., Gemini) and Vertex AI Studio
Deep understanding and practical experience in designing and building Retrieval-Augmented Generation (RAG) architectures
Experience with DevOps tooling (e.g., GitHub, Azure DevOps) and CI/CD for machine learning (MLOps)
Experience with diagramming tools (e.g. Visio)
Strong Experience in cloud native, deploying within cloud environments, serverless development and/or container-based solutions
Knowledge of the Model Context Protocol and its application in enabling LLMs to interact with external tools and data preferred
Familiarity with Agentic AI concepts and frameworks (e.g., LangChain) for building autonomous and multi-agent systems preferred
Experience interfacing with or working within CRM, ERP, eCommerce, or EMR/EHR solutions and common integration patterns
Strong Understanding of agile methodology and software development lifecycles preferred
Ability to sit for long periods of time
Mandatory Skills
Production GenAI experience
Vertex AI / Gemini expertise
hands-on RAG architecture
vector/embedding pipelines