AI Engineer

Title: AI Engineer

Location: Jacksonville, FL (32256)

Duration: 12+ Months (Contract to Hire)

Work Mode: Onsite

Position Summary

Seeking a hands-on AI Engineer to turn high-value business workflows into secure, reliable AI applications. This person will work across enterprise AI, software engineering and system integration—building LLM-powered applications, agents, enterprise knowledge base and automation that connect knowledge, cloud services and enterprise platforms to real operational workflows.

This is not primarily a foundation-model research role. The engineer should be a pragmatic builder who can move quickly from business problem to working prototype, validate measurable business value with stakeholders, and then harden successful solutions for production. That operating model mirrors focus on leveraging existing AI platforms, integrating systems and data, focusing on high-ROI scenarios.

What You’ll Be Doing :

• Partner with Product, Customer Support, SE/Integration, RCD, Operations and other business teams to identify repetitive or high-friction workflows where AI can create measurable customer or employee value.
• Rapidly prototype AI-enabled applications, assistants and automations, validate them with real users, and convert successful prototypes into maintainable production solutions.
• Build backend services and AI workflows using Python, REST APIs and modern LLM APIs; use structured outputs, tool/function calling and agent orchestration where appropriate.
• Build grounded knowledge experiences using RAG, embeddings, search and enterprise knowledge sources, including product documentation, Atlassian Confluence pages, support knowledge and structured business data.
• Design and implement AI agents and tool integrations, including MCP-style interfaces where appropriate, that can safely query approved and third-party systems.
• Create reusable connectors and services rather than one-off scripts, with particular attention to APIs, authentication, role-based access, secrets management and auditability.
• Build evaluation suites for AI workflows, including groundedness/relevance, hallucination or unsupported-answer rates, retrieval quality, tool-selection accuracy, tool-execution success, escalation behavior, latency and cost.
• Instrument production AI systems with logs, traces, metrics, failure analysis and usage/adoption telemetry; use the data to continuously improve quality and ROI.
• Apply security-by-design to AI integrations. Mutating, high-risk or sensitive actions should use explicit authorization and human approval, consistent with AI security policies.
• Document architectures, prompts/context strategies, evaluation datasets, API contracts and reusable patterns so other engineers can maintain and extend what is built.
• Stay current on AI models and engineering approaches, but recommend technology based on reliability, security, cost and business value.

Basic Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical field.
• 2+ years of relevant software, AI/ML or applied-AI engineering experience;
• Proficient Python programming and software-engineering fundamentals.
• Git, automated testing, debugging and clean-code practices
• Hands-on experience with AWS or other cloud platforms such as Microsoft Azure or Google Cloud.
• Ability to build, debug and test backend applications and REST APIs
• Hands-on project experience building AI applications using production LLM APIs, managed GenAI platforms, or AI development tools such as ChatGPT, Atlassian Rovo, Microsoft Copilot and Cursor/kiro.
• Understanding of core AI and Generative AI concepts, including LLMs, prompting and context management, embeddings, RAG, vector search, grounding techniques, agent tool-use, agent skills, agent memory, MCP Protocol, Agentic AI, AI evaluation, and AI security, etc.
• Experience designing and conducting tests or evaluations for AI output
• Working familiarity with cloud deployment, Docker, CI/CD or equivalent production engineering practices; Experience with infrastructure-as-code tools such as Terraform is a plus.
• Security-aware engineering mindset: application and AI security, authentication, permissions, audit logging and safe handling of enterprise data
• Ability to understand business needs, turn them into clear technical solutions, and communicate effectively with business stakeholders.

Preferred Qualifications:

• Experience in payments, fintech, POS/terminal systems, merchant technology or another regulated enterprise environment
• Experience implementing MCP clients/servers or equivalent model-to-tool integration
• Demonstrated experience building agentic workflow involving tool use, orchestration, or multi-step automation.
• Experience with agent frameworks or orchestration SDKs such as LangGraph, LangChain, Strands, AutoGen, CrewAI, or equivalent orchestration experience
• Experience with cloud AI/GenAI services such as Amazon Bedrock, AWS agentic AI services, or comparable services on Microsoft Azure or Google Cloud.
• Working familiarity with SQL and Python data-processing libraries such as Pandas or NumPy, with experience working with structured data and data integrations.
• Familiarity with PCI-DSS, payments security or enterprise security controls
• Experience building adoption/enablement tools that business teams can use
• Experience with Jira/Atlassian integrations, contact-center (Amazon Connect) automation or enterprise support tooling
• AI evaluation/observability platforms or custom evaluation pipelines
• Knowledge of Android/payment-terminal ecosystems
• Public portfolio, open-source contribution or demonstrable side project showing a production-quality AI application
• One or more relevant industry-recognized certifications in cloud, AI, or cybersecurity, such as AWS Certified Generative AI Developer – Professional, AWS Certified Solutions Architect – Professional, AWS Certified DevOps Engineer – Professional, CompTIA Security+, ISC2 CISSP or CCSP, or comparable Microsoft Azure or Google Cloud certifications.

Dexian stands at the forefront of Talent + Technology solutions with a presence spanning more than 70 locations worldwide and a team exceeding 10,000 professionals.

As one of the largest technology and professional staffing companies and one of the largest minority-owned staffing companies in the United States, Dexian combines over 30 years of industry expertise with cutting-edge technologies to deliver comprehensive global services and support.

Dexian connects the right talent and the right technology with the right organizations to deliver trajectory-changing results that help everyone achieve their ambitions and goals. To learn more, please visit https://dexian.com/.

Dexian is an Equal Opportunity Employer that recruits and hires qualified candidates without regard to race, religion, sex, sexual orientation, gender identity, age, national origin, ancestry, citizenship, disability, or veteran status.