AI Solutions Developer (Remote)

OpenKrill; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Geotab is seeking an AI Solutions Developer to architect, build, and operationalize AI applications and agents for Global Enablement. You will implement secure APIs, RAG systems, and full-stack solutions that improve learning, sales enablement, and operational efficiency across the organization.

You will work with Python, LangChain, and AI frameworks, building scalable backend services, and collaborating with IT and GenAI platform teams to align with infrastructure standards.

Qualifications

• Proficient Python development for AI applications.
• Experience building AI agents, automation, and RAG systems.
• Able to design secure, scalable backend services.

Responsibilities

• Architect, code, and deploy AI agents and automation using Python and LangChain/AutoGen.
• Develop backend logic and microservices to support AI workflows.
• Build and integrate retrieval augmented generation (RAG) systems with vector databases.
• Create AI applications with intuitive UIs and secure integrations.
• Establish CI/CD pipelines and security best practices for production release.

Skills

Python

LangChain

AI systems

CI/CD

REST APIs

Tools

PostgreSQL

pgvector

Pinecone

Weaviate

Job description

Who we are:

Geotab ® is a global leader in IoT and connected transportation and certified “Great Place to Work™.” We are a company of diverse and talented individuals who work together to help businesses grow and succeed, and increase the safety and sustainability of our communities.

Geotab is advancing security, connecting commercial vehicles to the internet and providing web-based analytics to help customers better manage their fleets. Geotab’s open platform and Geotab Marketplace ®, offering hundreds of third-party solution options, allows both small and large businesses to automate operations by integrating vehicle data with their other data assets. Processing billions of data points a day, Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety and achieve strong compliance to regulatory changes.

Our team is growing and we’re looking for people who follow their passion, think differently and want to make an impact. Ours is a fast paced, ever changing environment. Geotabbers accept that challenge and are willing to take on new tasks and activities - ones that may not always be described in the initial job description. Join us for a fulfilling career with opportunities to innovate, great benefits, and our fun and inclusive work culture. Reach your full potential with Geotab. To see what it’s like to be a Geotabber, check out our blog and follow us @InsideGeotab on Instagram.

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking an AI Solutions Developer who will be responsible for architecting, building, and operationalizing custom AI applications, agents, self-service tools, and automated workflows that help our Global Enablement teams work smarter, support revenue generation, and deliver measurable ROI. This is a hands‑on engineering role for a builder who loves turning ideas into secure, reliable, production‑ready solutions. If you love building with AI, and are keen to join an industry leader — we would love to hear from you!

What you’ll do:

As an AI Solutions Developer your key area of responsibility will be designing, developing, deploying, and maintaining AI‑powered applications that strengthen sales enablement, learning design, customer education, and operational efficiency across Global Enablement. You will be responsible for coding custom AI agents and automation solutions in Python, building retrieval augmented generation (RAG) systems, developing full‑stack applications with intuitive user interfaces, and integrating AI with business systems through secure APIs. You could be building an AI trainer that supports learning and skill development, a sales enablement engine that curates the right content, pitch decks, talk tracks, and positioning for each seller’s needs, or automated workflows that create and update training, videos, and user guides as our products evolve. You will also need to establish engineering best practices, CI/CD pipelines, AI evaluation processes, and security guardrails, while monitoring performance and cost to keep solutions reliable and efficient. You will need to work closely with subject matter experts across enablement functions to translate specialized knowledge and learning objectives into practical applications, and partner with IT and GenAI platform teams to ensure your solutions align with company infrastructure and technology standards.

To be successful in this role you will be an independent problem solver and a strong communicator who can explain technical capabilities, limitations, risks, and tradeoffs clearly to nontechnical stakeholders. You take ownership of your work from initial concept through deployment and ongoing operation, and you balance technical capability with usability and measurable business value. In addition, the successful candidate will have the ability to translate loosely defined business requirements into precise technical specifications, along with a disciplined approach to documentation and a passion for staying current in a rapidly evolving AI landscape.

How you’ll make an impact:

• Architect, code, and deploy custom AI agents and automation solutions using Python and relevant frameworks, such as LangChain and AutoGen, to solve complex business challenges within Global Enablement.


• Develop and maintain backend logic and microservices required to support AI workflows, ensuring high availability and scalability of deployed agents.


• Build custom retrieval augmented generation (RAG) systems by integrating large language models (LLMs) with PostgreSQL with pgvector and vector databases such as Pinecone and Weaviate, enabling secure interaction with proprietary data and approved content.


• Write clean, maintainable, and efficient code for content generation, localization, and multimedia processing automations, adhering to software development best practices, including version control, code reviews, and testing.


• Develop complete AI applications, including intuitive user interfaces, backend services, and secure integrations for internal and external users.


• Implement conversation management, context retention, structured outputs, and tool calling to support interactive learning, guidance, and multi step workflows.


• Evaluate and integrate conversational AI, speech recognition, speech generation, interactive avatars, and multilingual capabilities.


• Build self service tools and AI supported workflows in partnership with subject matter experts, incorporating appropriate review and approval steps.


• Design and implement secure RESTful API integrations to connect AI agents with business systems, learning and sales enablement platforms, knowledge repositories, and third party platforms.


• Develop reusable code libraries, API wrappers, and solution frameworks to accelerate technical development across Global Enablement and ensure consistency in the codebase.


• Collaborate with IT and GenAI platform teams to ensure departmental solutions align with company infrastructure and technology standards, leveraging cloud resources such as Google Vertex AI, Azure, and AWS effectively.


• Develop knowledge ingestion and synchronization processes to keep connected content current, approved, and appropriate for its intended audience.


• Implement authentication, authorization, and role based access controls for internal, partner, and customer facing applications.


• Design solutions that support future integrations and additional enablement use cases without unnecessary duplication or redevelopment.


• Implement code level security measures to ensure agents handling sensitive information, including internal documents and customer data, adhere to data privacy and responsible AI guardrails.


• Establish continuous integration and continuous deployment (CI/CD) pipelines for testing and deploying AI agents, ensuring rigorous quality control and risk mitigation before production release.


• Monitor technical performance metrics, including latency, token usage, and error rates, and optimize code to ensure cost efficiency and response quality.


• Establish AI evaluation processes to test answer accuracy, retrieval quality, relevance, and appropriate handling of unsupported requests.


• Implement safeguards against unauthorized information access, prompt injection, and unintended actions, including human approval and escalation where appropriate.


• Maintain separation of internal, partner, and customer facing content, with appropriate controls to protect information across users and organizations.


• Maintain deployed solutions through monitoring, troubleshooting, updates, and continuous improvement.


• Document deployment procedures, support requirements, and operational handover processes to ensure continuity.


• Translate complex business requirements from Global Enablement stakeholders into detailed technica