- Company Name
- Newpage Solutions
- Job Title
- AI Engineer
- Job Description
-
**Job Title:** AI Engineer
**Role Summary:**
Design, develop, and deploy production‐grade Generative AI and agentic applications. Lead end‑to‑end AI initiatives, from model selection and orchestration to scalable cloud deployments, while ensuring optimal performance, cost, and security. Own the full AI lifecycle, from RAG pipelines and prompt engineering to microservice architecture and observability.
**Expectations:**
- Deliver high‑quality, maintainable code in a fast, independent capacity.
- Drive continuous improvement of AI systems, staying current on emerging models, frameworks, and best practices.
- Act as a technical leader across cross‑functional teams.
**Key Responsibilities:**
- Architect and implement generative AI solutions using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, and custom orchestration layers.
- Build and optimize Retrieval‑Augmented Generation (RAG) pipelines with vector databases (Pinecone, ChromaDB, Weaviate, pgvector).
- Design multi‑modal workflows integrating text, image, voice, and video.
- Develop robust prompt and context engineering frameworks to enhance accuracy, latency, and cost efficiency.
- Create microservices and modular backends in Python, JavaScript, or Java following SOLID, DDD, and clean architecture principles.
- Deploy AI services on AWS, GCP, or Azure using Docker, Kubernetes, or serverless models.
- Integrate event‑driven systems (Kafka, MSK, SQS) and relational/graph databases.
- Leverage AI‑assisted development tools (Claude Code, GitHub Copilot, Cursor) to accelerate coding while maintaining quality.
- Construct POCs, research experiments, and innovation sprints to evaluate new AI techniques.
**Required Skills:**
- 5+ years software development; 2+ years AI/ML systems engineering or generative AI.
- Deep knowledge of LLMs, prompt engineering, and context optimization.
- Proficiency in Python or JavaScript with solid OOP, SOLID, and 12‑factor application experience.
- Proven track record building and deploying GenAI/LLM systems in production.
- Experience with vector databases, RAG, microservice architecture, and cloud native deployments.
- Familiarity with AI development assistants and structured workflows.
- Strong problem‑solving, independent work ethic, and cross‑team collaboration.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related technical field.
- Relevant certifications in AI/ML, cloud platforms, or data engineering preferred but not mandatory.