AI Engineer (Remote)

Invoke is a consulting and Innovation firm focused on delivering Intelligent automation solutions that solve real operational challenges. We partner with organizations across industries, including the public sector, to design and implement scalable RPA and AI-driven workflows that improve efficiency, accuracy, and reliability. Our teams work hands-on with clients to automate complex processes across a range of systems, from modern applications to legacy environments. A significant portion of our work is within the public sector, where we help government organizations streamline high-volume processes, improve data quality, and modernize critical operations through automation. INVOKE provides the technology, implementation, and lifecycle expertise to solve business challenges through the lens of intelligent automation technologies like Robotic Process Automation and Artificial Intelligence. As this role supports public sector clients, U.Build LLM-powered automations , chat/voice assistants, and intelligent agents that integrate seamlessly with client systems. Design and deploy retrieval-augmented generation (RAG) pipelines, including document ingestion, chunking, embeddings, vector search, and grounding for accurate, auditable responses. Implement tool/function calling and multi-step agent workflows to perform actions (draft → review → execute → verify), incorporating human-in-the-loop processes where necessary. FastAPI or Node.js ) with tests, observability, and CI/CD pipelines; deploy to the cloud using serverless or containerized architectures. Instrument, evaluate, and tune LLM solutions—manage tracing, latency and cost budgets, prompt/version control, A/B tests, and golden-set evaluations to reduce hallucinations and improve output quality. Implement guardrails and safety mechanisms , including content filters, PII redaction, schema/JSON validation, fallbacks, and model routing across providers. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. ~2–3 years of experience in software engineering using one or more programming languages: Python, Java, Node.js, C#, or similar. ~1–2 years of hands-on experience building with LLMs —prompt engineering, RAG, agents, tool/function calling, structured outputs, and streaming. ~ OpenAI/Azure OpenAI, Anthropic, Google, LangChain, LlamaIndex) and vector databases (e.g., Experience preparing unstructured data (PDFs, HTML, emails, tickets) and developing robust ingestion/embedding pipelines and document stores (e.g., LangSmith, RAGAS/DeepEval, OpenTelemetry, logging) and experience writing automated tests for LLM workflows. ~ Basic DevOps/MLOps skills: Docker, Kubernetes or serverless (Lambda, Cloud Run), CI/CD (GitHub Actions), and secrets/IAM best practices. ~ Exposure to cloud platforms (AWS, Azure, GCP) and related services (API Gateways, managed databases/queues; Experience integrating with enterprise applications and knowledge bases, and developing lightweight admin UIs (React, Next.js) for internal tools.