AI Solutions Developer

Geotab • Atlanta, GA

10h • Hybrid

About The Position

Geotab is seeking an AI Solutions Developer to architect, build, deploy, and operate custom AI applications, agents, self-service tools, and automated workflows for its Global Enablement teams. The role focuses on supporting sales enablement, learning design, customer education, revenue generation, and operational efficiency through secure, reliable, production-ready AI solutions.

The developer will build Python-based AI agents and automation, retrieval-augmented generation systems, full-stack applications, and secure integrations with business systems. Solutions may include AI learning trainers, sales content and guidance tools, and workflows for generating and updating training materials, videos, and user guides. The role also establishes engineering practices, CI/CD pipelines, AI evaluation processes, security safeguards, and monitoring to ensure quality, reliability, and cost efficiency.

This is a hands-on engineering role requiring ownership from initial concept through deployment and ongoing operations. The developer translates business needs and specialized subject-matter knowledge into technical specifications and usable applications, collaborates with enablement stakeholders, IT, and GenAI platform teams, and communicates technical capabilities, limitations, risks, and tradeoffs to nontechnical audiences. The position supports a flexible hybrid work model; specific office-location and attendance expectations will be shared during hiring.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related quantitative field.
• 3–5 years of experience in AI/ML, Data Science, or software engineering, focused on building and deploying intelligent systems or automation.
• Strong proficiency in Python, including pandas and asynchronous programming.
• Working proficiency in JavaScript or TypeScript for user-facing applications.
• Hands-on experience building multi-step agentic workflows with code-first frameworks such as LangChain, AutoGen, or CrewAI.
• Experience integrating LLM APIs such as OpenAI, Gemini, and Anthropic.
• Demonstrated experience designing RAG pipelines using PostgreSQL with pgvector and vector databases or search libraries such as Pinecone, Weaviate, and FAISS.
• Experience deploying applications in Google Cloud, including Vertex AI and Cloud Functions.
• Knowledge of Git, testing, CI/CD, RESTful APIs, and secure coding practices.
• Ability to translate loosely defined business requirements into precise technical specifications.
• Ability to solve problems independently, take ownership from concept through ongoing operation, and communicate technical capabilities, limitations, risks, and tradeoffs clearly to nontechnical stakeholders.
• Disciplined documentation practices and interest in staying current with developments in AI.

Nice To Haves

• Master’s degree in a related field.
• Professional certifications in Google Cloud, Azure, AWS, or specific AI technologies.
• Experience with speech, avatar, or multilingual capabilities.

Responsibilities

• Architect, code, deploy, and maintain custom AI agents and automation solutions using Python and relevant frameworks.
• Develop and maintain backend logic and scalable, highly available microservices for AI workflows.
• Build RAG systems integrating LLMs with PostgreSQL/pgvector and vector databases or search libraries.
• Write clean, maintainable code for content generation, localization, and multimedia processing, following version control, code review, and testing practices.
• Develop complete AI applications with user interfaces, backend services, and secure integrations.
• Implement conversation management, context retention, structured outputs, and tool calling for interactive and multi-step workflows.
• Evaluate and integrate conversational AI, speech recognition and generation, interactive avatars, and multilingual capabilities.
• Build self-service tools and AI-supported workflows with subject matter experts, including appropriate review and approval steps.
• Design secure REST API integrations with business systems, learning and sales platforms, knowledge repositories, and third-party platforms.
• Develop reusable libraries, API wrappers, and solution frameworks for consistent and accelerated development.
• Collaborate with IT and GenAI platform teams to align solutions with company infrastructure and technology standards, using cloud resources effectively.
• Develop knowledge ingestion and synchronization processes to keep connected content current, approved, and audience-appropriate.
• Implement authentication, authorization, and role-based access controls for internal, partner, and customer-facing applications.
• Design extensible solutions that support future integrations and enablement use cases.
• Implement code-level security, data privacy, and responsible AI safeguards for sensitive information.
• Establish CI/CD pipelines and quality controls for testing and deploying AI agents.
• Monitor latency, token usage, error rates, and other performance measures; optimize cost and response quality.
• Establish evaluation processes for answer accuracy, retrieval quality, relevance, and handling of unsupported requests.
• Protect against unauthorized information access, prompt injection, and unintended actions, using human approval or escalation where appropriate.
• Maintain separation and protection of internal, partner, and customer-facing content.
• Monitor, troubleshoot, update, and continuously improve deployed solutions.
• Document deployment procedures, support requirements, and operational handover processes.
• Translate stakeholder needs into technical specifications and architecture designs supporting revenue generation, sales readiness, training, and operational efficiency.
• Assess technical feasibility and determine whether use cases are best served by custom code, existing platform configuration, or a combination.
• Research and prototype emerging AI technologies, LLM releases, and agent frameworks.
• Partner with subject matter experts to translate specialized knowledge, learning objectives, and business processes into AI applications.
• Validate solution accuracy, instructional quality, usability, and effectiveness with experts and end users.
• Define scopes, delivery phases, dependencies, and success criteria, and communicate technical risks and tradeoffs.
• Identify opportunities to automate repetitive work and create self-service experiences, choosing AI or conventional automation as appropriate.
• Evaluate consolidation or replacement of existing applications with AI-enabled solutions, considering functionality, cost, security, migration, and support.
• Measure impact through adoption, time saved, quality improvements, operating costs, and agreed enablement outcomes.

Benefits

• Flexible working arrangements.
• Home office reimbursement program.
• Baby bonus and parental leave top-up program.
• Online learning and networking opportunities.
• Electric vehicle purchase incentive program.
• Competitive medical and dental benefits.
• Retirement savings program.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level