Artificial Intelligence Engineer

About the role

The Artificial Intelligence Engineer will design, develop, integrate, and deploy AI‑powered applications and autonomous agents that boost productivity, automate complex workflows, and improve decision‑making across the organization. The focus is on building secure, scalable agentic AI that can reason, retrieve information, interact with enterprise systems, and execute multi‑step tasks with appropriate human oversight.

Key responsibilities

• Design and implement single‑agent and multi‑agent solutions for enterprise business processes.
• Build agent architectures using large language models (LLMs), tool calling, memory, planning, reasoning, and retrieval‑augmented generation (RAG).
• Develop AI copilots, assistants, and intelligent automation integrated into existing workflows such as proposal preparation, engineering QA/QC, project management, finance, procurement, HR, and IT service management.
• Create secure integrations between AI agents and enterprise platforms via APIs, SDKs, web services, databases, and automation frameworks.
• Construct RAG and knowledge‑engineering pipelines, including document ingestion, chunking, embeddings, indexing, retrieval, and reranking.
• Produce production‑grade Python solutions, including APIs, microservices, backend services, and orchestration components.
• Implement testing, CI/CD, version control, monitoring, logging, observability, and scalable deployment practices.
• Apply governance, security, privacy, and responsible AI controls to mitigate prompt injection, data leakage, and unauthorized actions.
• Establish evaluation frameworks to continuously improve agent accuracy, reliability, latency, cost efficiency, and user adoption.
• Collaborate with business, IT, engineering, cybersecurity, data, and functional teams to translate requirements into practical AI solutions.

Required profile

• Bachelor’s or Master’s degree in Computer Science, AI, Software Engineering, Data Science, or a related discipline.
• 3–7+ years of experience in software engineering, AI/ML, data engineering, or a related field.
• Strong programming skills in Python.
• Deep understanding of LLMs, generative AI, APIs, databases, distributed systems, and software architecture.
• Hands‑on experience building applications with LLM APIs, AI agents, or agentic workflows.
• Proficiency with Git, CI/CD pipelines, testing, and modern software‑development practices.
• Familiarity with cloud or private‑cloud deployment architectures.

Required skills

• Python
• LLM APIs and SDKs
• Prompt engineering
• Retrieval‑Augmented Generation (RAG)
• Vector databases
• Agentic AI frameworks
• Git
• CI/CD
• Testing frameworks
• Cloud deployment (public or private)
• APIs and microservices
• Distributed systems
• Software architecture