Lead AI Engineer

Job highlights Identified by Google from the original job post Qualifications • 7+ years of full software development lifecycle experience including design, development, testing, deployment, and support • Strong Python development experience • Deep understanding of object-oriented design principles, design patterns, and scalable architecture • Proven experience designing and implementing APIs and backend services • Hands-on experience building and deploying applications in Azure and/or Google Cloud Platform • Strong understanding of cloud scaling concepts and distributed systems • 2+ years of experience building LLM-based applications • Experience implementing RAG architectures, embeddings, vector databases, agents, and fine-tuning • Experience with LLM orchestration frameworks such as LangChain or LlamaIndex • Hands-on experience integrating OpenAI / Azure OpenAI / Google GenAI APIs • Experience with containerization and orchestration (Docker, Kubernetes) • Familiarity with version control tools such as Git / Azure DevOps • Experience writing Azure DevOps YAML pipelines for CI/CD • Experience with at least one additional object-oriented language such as Java, C#, or C++ • Strong communication skills and ability to work both independently and within collaborative engineering teams • AWS cloud experience • Experience with Databricks or Apache Spark • Knowledge of data warehousing and data lake architectures • Experience working with relational databases and SQL • Terraform infrastructure-as-code experience • Experience building AI platform components or internal developer platforms • Bachelor’s degree in Computer Science, Information Systems, or a related technical field • 19 more items(s) Responsibilities • In this role, you will help design and implement scalable AI-driven services within a modern cloud environment, working closely with engineering teams to build APIs, optimize inference pipelines, and deliver production-ready GenAI applications • Primarily a backend engineering role focused on AI platform development • 30% optimization, support, and enhancements • Daily Responsibilities • Design and implement scalable APIs and shared software services using Python • Build and support applications on an AI platform leveraging modern GenAI technologies • Develop LLM-powered applications using tools like LangChain or LlamaIndex • Work with Azure OpenAI and/or Google GenAI APIs to integrate LLM capabilities into production systems • Build cloud-native applications in Azure and GCP • Implement serverless architectures and containerized workloads using Docker and Kubernetes • Design, monitor, and optimize AI inference and data pipelines to improve performance and efficiency • Troubleshoot issues across application code, cloud environments, and AI services • Document architecture, APIs, and internal AI platform components • Collaborate with internal engineering and support teams to deliver scalable AI-driven solutions • Contribute to architecture discussions and continuously improve system performance, security, and scalability • Develop proof-of-concepts (POCs) to evaluate emerging AI technologies and their potential business impact • 13 more items(s) More job highlights Job description We are looking for a Senior Python / GenAI Engineer with strong experience building cloud-native applications and developing solutions powered by large language models. In this role, you will help design and implement scalable AI-driven services within a modern cloud environment, working closely with engineering teams to build APIs, optimize inference pipelines, and deliver production-ready GenAI ...applications.

Full Desk, Direct Hire role.

Hybrid opportunity in the Houston area.

Primarily a backend engineering role focused on AI platform development.

What you will be doing

Tech Breakdown

70% new development

30% optimization, support, and enhancements

Daily Responsibilities

• Design and implement scalable APIs and shared software services using Python

• Build and support applications on an AI platform leveraging modern GenAI technologies

• Develop LLM-powered applications using tools like LangChain or LlamaIndex

• Work with Azure OpenAI and/or Google GenAI APIs to integrate LLM capabilities into production systems

• Build cloud-native applications in Azure and GCP

• Implement serverless architectures and containerized workloads using Docker and Kubernetes

• Design, monitor, and optimize AI inference and data pipelines to improve performance and efficiency

• Troubleshoot issues across application code, cloud environments, and AI services

• Document architecture, APIs, and internal AI platform components

• Collaborate with internal engineering and support teams to deliver scalable AI-driven solutions

• Contribute to architecture discussions and continuously improve system performance, security, and scalability

• Develop proof-of-concepts (POCs) to evaluate emerging AI technologies and their potential business impact

Experience / Requirements

• 7+ years of full software development lifecycle experience including design, development, testing, deployment, and support

• Strong Python development experience

• Deep understanding of object-oriented design principles, design patterns, and scalable architecture

• Proven experience designing and implementing APIs and backend services

• Hands-on experience building and deploying applications in Azure and/or Google Cloud Platform

• Strong understanding of cloud scaling concepts and distributed systems

• 2+ years of experience building LLM-based applications

• Experience implementing RAG architectures, embeddings, vector databases, agents, and fine-tuning

• Experience with LLM orchestration frameworks such as LangChain or LlamaIndex

• Hands-on experience integrating OpenAI / Azure OpenAI / Google GenAI APIs

• Experience with containerization and orchestration (Docker, Kubernetes)

• Familiarity with version control tools such as Git / Azure DevOps

• Experience writing Azure DevOps YAML pipelines for CI/CD

• Experience with at least one additional object-oriented language such as Java, C#, or C++

• Strong communication skills and ability to work both independently and within collaborative engineering teams

Nice to Have

• AWS cloud experience

• Experience with Databricks or Apache Spark

• Knowledge of data warehousing and data lake architectures

• Experience working with relational databases and SQL

• Terraform infrastructure-as-code experience

• Experience building AI platform components or internal developer platforms

Education

Bachelor’s degree in Computer Science, Information Systems, or a related technical field

Posted By: Joshua Cairns Show full description Report this listing Loading...