- Company Name
- MRJ Recruitment
- Job Title
- AI Engineer
- Job Description
-
Job title: AI Engineer
Role Summary:
Design, build, and ship end‑to‑end AI‑first products for a diverse client portfolio, including LLM‑powered systems, agent frameworks, and conversational experiences. Own the entire product lifecycle—from discovery and rapid prototyping to scalable, enterprise‑ready delivery—while translating real user problems into pragmatic technical solutions.
Expectations:
- Deliver production‑grade LLM solutions that users depend on.
- Own the full product lifecycle and ensure smooth, scalable deployment.
- Embed AI capabilities within products and teams so value stays internal.
- Constantly experiment with new models, SDKs, and platforms, distinguishing production‑ready technology from hype.
Key Responsibilities:
- Research, prototype, and iterate on AI models and prompt engineering.
- Design and implement LLM orchestration and agent‑based frameworks (e.g., LangChain, LlamaIndex, AutoGen, custom solutions).
- Build APIs, event‑driven architectures, data pipelines, and automation integrations (e.g., UiPath, Blue Prism).
- Deploy models and services to cloud environments, ensuring reliability, scalability, and security.
- Collaborate with product and engineering teams to translate user challenges into technical deliverables.
- Conduct rapid prototyping, followed by rigorous testing and production rollout.
- Evaluate emerging AI tools and platforms for fit and readiness.
Required Skills:
- Strong software engineering background (Python, TypeScript/JavaScript, or Java).
- Proven experience shipping AI‑powered products to production.
- Deep familiarity with LLMs (Claude, GPT‑4/4.1, Gemini, and open‑source alternatives).
- Expertise in LLM orchestration, agent frameworks, prompt engineering, RAG, and multi‑agent workflows.
- Experience integrating AI into APIs, event‑driven architectures, data pipelines, and automation platforms (UiPath, Blue Prism).
- Knowledge of CI/CD, containerization (Docker, Kubernetes), and cloud services (AWS, GCP, Azure).
- Strong Git/GitHub workflow and repository management.
- Ability to experiment, evaluate, and implement new AI models and SDKs.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI/ML, or related field.
- No specific certifications required; relevant cloud or AI certifications preferred.