AI Engineer (GenAI/Agentic Systems)

As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for:

AI Engineer (GenAI/Agentic Systems)

Responsibilities:

• Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources

• Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation

• Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs

• Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed

• Partner with other engineers to set direction, mentor, and unblock the team – helping establish strong foundations for the AI initiative

• Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads

• Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation

• Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI

Requirements:

• 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms)

• Proven ability to ship production-grade LLM applications (RAG, tool/function calling, agent orchestration) with reliability, security, and observability

• Proficiency in at least one backend language used for AI systems (Python preferred) and comfort integrating with enterprise stacks (C#/.NET is a plus)

• Hands-on experience building and integrating RESTful APIs; GraphQL experience is a plus

• Experience integrating with external services and internal platforms via APIs and event-driven patterns

• Hands-on experience building LLM-powered applications end-to-end: prompt design, tool/function interfaces, structured outputs, and streaming user experiences

• Experience with RAG systems: document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation

• Experience with agentic frameworks and orchestration concepts (planning, routing, tool use, human-in-the-loop interruptions)

• Frameworks may include LangGraph, LangChain, Microsoft Semantic Kernel, or equivalent

• Experience working with model platforms (e.g., Azure OpenAI/OpenAI or similar) and designing for reliability (timeouts, fallbacks, quotas)

• Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights)

• Experience with search and retrieval services (Azure AI Search or similar) and building scalable, network-bound workloads

• Hands-on experience with CI/CD and automated deployments (Azure DevOps preferred), including containerization (Docker)