Job description
Description
abra professional services is seeking for an AI Engineer (GenAI & Integration)
The AI Engineer (GenAI & Integration) designs, builds, and deploys AI-powered solutions within enterprise systems and business workflows.
The role focuses on practical application of AI by integrating models, data, and tools into real operational environments to enable automation, decision support, and productivity gains.
The role emphasizes implementation and integration rather than model development, bridging AI capabilities with enterprise systems and workflows.
Key Responsibilities
Design and implement end-to-end AI solutions aligned with business needs
Integrate AI capabilities with enterprise systems, APIs, and data platforms, including legacy environments
Develop AI agents and automation workflows for multi-step task execution
Build AI-driven applications, including copilots and decision-support tools
Develop and maintain integration layers, including MCP-based and similar AI integration services
Evaluate, test, and validate AI outputs to ensure accuracy, reliability, and quality in production
Deploy, monitor, and optimize AI solutions in production environments
Maintain clear and structured documentation across solutions, integrations, and processes
Lead implementation of AI solutions in collaboration with business, IT, and engineering teams to ensure scalable and compliant delivery
Requirements
Required Skills
3+ years of hands-on software development experience, preferably in Python/backend or integration-focused roles, including practical experience with GenAI technologies such as LLMs, RAG, AI agents, and automation workflows. Proven ability to independently design, build, and deploy end-to-end production-grade solutions within complex enterprise environments.
Strong programming skills (Python preferred)
Hands-on experience with LLMs, prompt design, and RAG solutions
Experience integrating AI systems with enterprise data, APIs, and services (e.g., MCP or similar)
Experience building AI agents and automation workflows
Proven ability to build and deliver production-grade systems end-to-end
Understanding of system design, deployment, and production environments
Experience validating and evaluating AI system outputs for quality and reliability
Basic project management capabilities to coordinate tasks, timelines, and cross-functional collaboration
Preferred Qualifications
Experience with enterprise platforms (e.g., ERP, CRM, M365)
Documentation skills for technical solutions, workflows, and integration processes
Exposure to cloud environments and AI/LLM orchestration frameworks
Understanding of secure development practices and AI governance considerations
Success Criteria
Delivery of production-ready AI solutions
Measurable impact on business processes and efficiency
Adoption and effective use of AI across teams
Reliability and stability of deployed AI systems in production
Is this role relevant for you?