AI Engineer with Gen AI & LLM & RAG

Workload: full-time

Work model: 100% Remote

Rate: to be negotiated

We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG).

• This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role.

• 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.

• Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team.

• Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability.

  
  

Main 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.

  
  

Key Requirements:

• Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems.

• Proficiency in at least one backend language used for AI systems (Python preferred).

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

• Strong understanding of distributed systems fundamentals: concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization.

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

• Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus.

• 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.

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

• Development practices experience: Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks).

  
  

Nice to Have:

• Direct experience with LangGraph and/or LangChain for multi-agent workflows.

• Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar).

• Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications.

• Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI.

• Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control).

  
  

Other Details:

This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.