AI Engineer
Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Feb 25, 2026.
Employment Type: Full-Time, Permanent Overview: We are looking for a Senior AI Engineer to design and deliver AI-powered capabilities within business applications. The role focuses on building reliable reasoning pipelines, intelligent workflows, and agent-driven systems that integrate enterprise data and automate complex processes.
Key
Responsibilities Design AI workflows that execute multi-step business tasks autonomously. Build agentic systems capable of planning, reasoning, and taking actions using tools and APIs. Develop multi-agent architectures where specialized agents collaborate to complete processes. Implement Retrieval-Augmented Generation (RAG) over enterprise data sources. Integrate LLMs via APIs and open-source models using provider-agnostic architecture. Design structured outputs, guardrails, and validation layers for reliable behavior. Build tool-using AI for database querying, document processing, and API orchestration. Create evaluation pipelines to measure accuracy, reliability, and regression of AI outputs. Implement observability including tracing, latency, and cost monitoring. Design failure handling, fallbacks, and human-in-the-loop workflows. Architect scalable async execution using queues and background workers. Own production reliability of AI features from deployment through monitoring. Evaluate approaches (RAG vs fine-tuning vs workflow vs agents) and justify design decisions. Define AI engineering standards and best practices across projects. Establish evaluation benchmarks and acceptance criteria for AI features. Participate in technical hiring and mentoring of future AI team members. Experience Minimum 5+ years software development experience with significant hands-on work building production AI systems. Experience delivering end-to-end AI features used by real users. Hands-on experience with RAG, agent workflows, or automation systems.
Technical Skills Strong Python programming skills. Experience with AI frameworks (LangChain, LlamaIndex, DSPy, Semantic Kernel, or similar). Understanding of agents, tool calling, and workflow orchestration patterns. Experience with vector databases and retrieval systems. Knowledge of evaluation methodologies for AI outputs. Experience integrating AI systems with APIs, databases, and backend applications. Familiarity with containerized deployments and cloud platforms. Good to Have Experience with multi-agent coordination patterns. LLMOps practices (versioning, rollback, evaluation datasets). Working with open-source/local models. Security and safety considerations in AI systems. Experience improving business workflows using AI automation.
Soft Skills Ability to work with ambiguous requirements and drive solution design. Strong debugging ability in non-deterministic systems. Clear communication and technical ownership.